W0219 01:46:19.215000 2110507 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0219 01:46:19.215000 2110507 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:19.215000 2110507 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0219 01:46:19.215000 2110507 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.051000 661040 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0219 01:46:20.051000 661040 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.051000 661040 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0219 01:46:20.051000 661040 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.085000 1982123 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0219 01:46:20.085000 1982123 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.085000 1982123 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0219 01:46:20.085000 1982123 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.201000 1983947 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0219 01:46:20.201000 1983947 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.201000 1983947 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0219 01:46:20.201000 1983947 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.203000 1990262 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0219 01:46:20.203000 1990262 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.203000 1990262 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0219 01:46:20.203000 1990262 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.209000 1986959 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0219 01:46:20.209000 1986959 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.209000 1986959 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0219 01:46:20.209000 1986959 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.213000 1988962 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0219 01:46:20.213000 1988962 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.213000 1988962 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0219 01:46:20.213000 1988962 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.226000 1987087 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0219 01:46:20.226000 1987087 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.226000 1987087 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0219 01:46:20.226000 1987087 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.278000 1987887 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0219 01:46:20.278000 1987887 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.278000 1987887 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0219 01:46:20.278000 1987887 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.329000 673195 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0219 01:46:20.329000 673195 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.329000 673195 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0219 01:46:20.329000 673195 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.420000 1985034 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0219 01:46:20.420000 1985034 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.420000 1985034 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0219 01:46:20.420000 1985034 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.456000 1983838 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0219 01:46:20.456000 1983838 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.456000 1983838 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0219 01:46:20.456000 1983838 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.517000 1985442 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0219 01:46:20.517000 1985442 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.517000 1985442 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0219 01:46:20.517000 1985442 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.557000 1986836 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0219 01:46:20.557000 1986836 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.557000 1986836 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0219 01:46:20.557000 1986836 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.722000 2033589 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0219 01:46:20.722000 2033589 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.722000 2033589 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0219 01:46:20.722000 2033589 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.773000 651329 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0219 01:46:20.773000 651329 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0219 01:46:20.773000 651329 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0219 01:46:20.773000 651329 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
PyTorch: setting up devices
PyTorch: setting up devices
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loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}


Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}


Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}


Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}


Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}


Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}


Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

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You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,

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    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.

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Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
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Loading checkpoint shards: 100%|██████████All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

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All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

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Loading checkpoint shards: 100%|██████████All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.81it/s]
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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.


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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
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All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.80it/s]All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

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Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.45it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.91it/s]
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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.77it/s]
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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:02<00:00,  3.19it/s]
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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.


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All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.80it/s]
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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.87it/s]
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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.80it/s]
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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.81it/s]
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All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.93it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.61it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.95it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.79it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.68it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.22it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
██████  | 4/5 [00:01<00:00,  3.32it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.37it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.26it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.30it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.23it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.22it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.21it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.85it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.77it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.43it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.82it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.45it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.76it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.31it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.72it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.33it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.77it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.40it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.89it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.42it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.55it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.15it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.60it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.31it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.79it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.40it/s]
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

�██  | 4/5 [00:01<00:00,  3.00it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.55it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.06it/s]

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.64it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.52it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.74it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.45it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.60it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.31it/s]
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.62it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.29it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.70it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.41it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.06it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.81it/s]
All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.47it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.01it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.67it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.41it/s]
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.10it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.77it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.17it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  2.55it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.56it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.22it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.82it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.68it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.83it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.70it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.68it/s]

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.45it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.45it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.04it/s]
All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.45it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.01it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.76it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.67it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.81it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.69it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.76it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.48it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.93it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.48it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.03it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.89it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.59it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.24it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.56it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.21it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.63it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.40it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.73it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.56it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.60it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.31it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:02<00:00,  3.06it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:02<00:00,  2.41it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.45it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.17it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.57it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.27it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.50it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.15it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.78it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.62it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.94it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.75it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.56it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.26it/s]

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.66it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.35it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.70it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.60it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.53it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.25it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.51it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.22it/s]
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.38it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  2.94it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.54it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.27it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.63it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.42it/s]

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.26it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.97it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.98it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.58it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.48it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.11it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.06it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  2.51it/s]

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.51it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.24it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.55it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.21it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.79it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.33it/s]
All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:02<00:00,  2.99it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:02<00:00,  2.36it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.54it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.28it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.65it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.37it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.72it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.61it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.37it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  2.97it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.35it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.00it/s]
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.43it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.13it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.14it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  2.56it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.33it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  2.98it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.81it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.36it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.15it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  2.57it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.52it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.18it/s]
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.51it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.19it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.90it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.57it/s]
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.09it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.89it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.52it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.24it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.05it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  2.53it/s]
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.47it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.27it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.59it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.28it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.22it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  2.92it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.63it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.27it/s]

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.01it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.86it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.42it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.17it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.54it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.55it/s]

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.19it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  2.84it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.18it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  2.84it/s]
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.17it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.94it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.28it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.16it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.21it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  2.90it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file added_tokens.json from cache at None
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file special_tokens_map.json from cache at None
loading file special_tokens_map.json from cache at None
loading file special_tokens_map.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file added_tokens.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file chat_template.jinja from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file special_tokens_map.json from cache at None
loading file chat_template.jinja from cache at None
loading file chat_template.jinja from cache at None
loading file chat_template.jinja from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file special_tokens_map.json from cache at None
loading file chat_template.jinja from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file added_tokens.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file special_tokens_map.json from cache at None
loading file special_tokens_map.json from cache at None
loading file chat_template.jinja from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file added_tokens.json from cache at None
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file special_tokens_map.json from cache at None
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file added_tokens.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file special_tokens_map.json from cache at None
loading file added_tokens.json from cache at None
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file chat_template.jinja from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file chat_template.jinja from cache at None
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file added_tokens.json from cache at None
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file special_tokens_map.json from cache at None
loading file added_tokens.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file special_tokens_map.json from cache at None
loading file chat_template.jinja from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file chat_template.jinja from cache at None
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file chat_template.jinja from cache at None
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file special_tokens_map.json from cache at None
loading file chat_template.jinja from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file special_tokens_map.json from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file chat_template.jinja from cache at None
loading file chat_template.jinja from cache at None
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file added_tokens.json from cache at None
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file added_tokens.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file special_tokens_map.json from cache at None
loading file chat_template.jinja from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
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Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Using custom data configuration default-5e4e9de28fd39dca
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Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
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Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
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Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
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Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
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Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
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Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
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Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
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Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Using custom data configuration default-5e4e9de28fd39dca
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Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
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Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
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Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
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Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
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Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
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Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Using custom data configuration default-5e4e9de28fd39dca
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Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
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Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
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Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Overwrite dataset info from restored data version if exists.
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1637: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Attempting to resume from /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-30000
Attempting to resume from /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-30000
Attempting to resume from /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-30000
Attempting to resume from /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-30000
Attempting to resume from /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-30000
Attempting to resume from /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-30000
Attempting to resume from /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-30000
Attempting to resume from /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-30000
Attempting to resume from /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-30000
Attempting to resume from /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-30000
Attempting to resume from /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-30000
Attempting to resume from /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-30000
Attempting to resume from /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-30000
Attempting to resume from /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-30000
Attempting to resume from /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-30000
Attempting to resume from /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-30000
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
  Continuing training from checkpoint, will skip to saved global_step
  Continuing training from epoch 0
  Continuing training from global step 30000
  Will skip the first 0 epochs then the first 30000 batches in the first epoch.
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
  Continuing training from checkpoint, will skip to saved global_step
  Continuing training from epoch 0
  Continuing training from global step 30000
  Will skip the first 0 epochs then the first 30000 batches in the first epoch.
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
  Continuing training from checkpoint, will skip to saved global_step
  Continuing training from epoch 0
  Continuing training from global step 30000
  Will skip the first 0 epochs then the first 30000 batches in the first epoch.
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
  Continuing training from checkpoint, will skip to saved global_step
  Continuing training from epoch 0
  Continuing training from global step 30000
  Will skip the first 0 epochs then the first 30000 batches in the first epoch.
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
  Continuing training from checkpoint, will skip to saved global_step
  Continuing training from epoch 0
  Continuing training from global step 30000
  Will skip the first 0 epochs then the first 30000 batches in the first epoch.
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
  Continuing training from checkpoint, will skip to saved global_step
  Continuing training from epoch 0
  Continuing training from global step 30000
  Will skip the first 0 epochs then the first 30000 batches in the first epoch.
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
  Continuing training from checkpoint, will skip to saved global_step
  Continuing training from epoch 0
  Continuing training from global step 30000
  Will skip the first 0 epochs then the first 30000 batches in the first epoch.
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
  Continuing training from checkpoint, will skip to saved global_step
  Continuing training from epoch 0
  Continuing training from global step 30000
  Will skip the first 0 epochs then the first 30000 batches in the first epoch.
  Continuing training from checkpoint, will skip to saved global_step
  Continuing training from epoch 0
  Continuing training from global step 30000
  Will skip the first 0 epochs then the first 30000 batches in the first epoch.
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
  Continuing training from checkpoint, will skip to saved global_step
  Continuing training from epoch 0
  Continuing training from global step 30000
  Will skip the first 0 epochs then the first 30000 batches in the first epoch.
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
  Continuing training from checkpoint, will skip to saved global_step
  Continuing training from epoch 0
  Continuing training from global step 30000
  Will skip the first 0 epochs then the first 30000 batches in the first epoch.
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
  Continuing training from checkpoint, will skip to saved global_step
  Continuing training from epoch 0
  Continuing training from global step 30000
  Will skip the first 0 epochs then the first 30000 batches in the first epoch.
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
  Continuing training from checkpoint, will skip to saved global_step
  Continuing training from epoch 0
  Continuing training from global step 30000
  Will skip the first 0 epochs then the first 30000 batches in the first epoch.
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
  Continuing training from checkpoint, will skip to saved global_step
  Continuing training from epoch 0
  Continuing training from global step 30000
  Will skip the first 0 epochs then the first 30000 batches in the first epoch.
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
  Continuing training from checkpoint, will skip to saved global_step
  Continuing training from epoch 0
  Continuing training from global step 30000
  Will skip the first 0 epochs then the first 30000 batches in the first epoch.
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
  Continuing training from checkpoint, will skip to saved global_step
  Continuing training from epoch 0
  Continuing training from global step 30000
  Will skip the first 0 epochs then the first 30000 batches in the first epoch.
Automatic Weights & Biases logging enabled, to disable set os.environ["WANDB_DISABLED"] = "true"
wandb: Currently logged in as: jchen169 to https://api.wandb.ai. Use `wandb login --relogin` to force relogin
wandb: Using wandb-core as the SDK backend.  Please refer to https://wandb.me/wandb-core for more information.
wandb: Tracking run with wandb version 0.19.6
wandb: Run data is saved locally in /opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/wandb/run-20250219_020918-b3we4gqr
wandb: Run `wandb offline` to turn off syncing.
wandb: Syncing run qwen-vl-diff-clip-16-nodes_early_pool2d_4
wandb: ⭐️ View project at https://wandb.ai/jchen169/huggingface
wandb: 🚀 View run at https://wandb.ai/jchen169/huggingface/runs/b3we4gqr
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)

  0%|          | 0/569592 [00:00<?, ?it/s]/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)
/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py:3119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint_rng_state = torch.load(rng_file)

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  warnings.warn(
:41:15,  6.91it/s]
                                                         

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  warnings.warn(
it]
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  5%|▌     /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90151490 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  warnings.warn(

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  warnings.warn(
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                                /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                          

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  5/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (93331640 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
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  warnings.warn(
9:28,  2.80s/it]
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  5%|▌         | 30290/5695/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
92 [13:09<347:00:55,  2.32s/it]
                                                          

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  5%|▌ /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
        | 30352/569592 [16:06<288:16:19,  1.92s/it]
                                                          

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  warnings.warn(
s/it]
                                                          

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  5%/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95971008 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  warnings.warn(
8s/it]
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  5%|▌  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (105785470 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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                                                /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98911692 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
          

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  warnings.warn(
t]
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  5%|▌         | 30745/569592 [34:00<318/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
:23:29,  2.13s/it]
  5%|▌         | 30746/569592 [34:03<352:55:18,  2.36s/it]
                                                          

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  5%|▌         | 30762/569592 [34:43<315:02:52,  2.10s/it]
                                                          

  5%|▌         | 3/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (99046487 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
0762/569592 [34:43<315:02:52,  2.10s/it]
  5%|▌         | 30763/569592 [34:48<447:35:12,  2.99s/it]
                                                          

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  5%|▌         | 30784/569592 [35:40<390:48:40,  2.61s/it]
  5%|▌         | 30785/569592 [35:41<331:21:13,  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
2.21s/it]
                                                          

  5%|▌         | 30785/569592 [35:41<331:21:13,  2.21s/it]
  5%|▌         | 30786/569592 [35:43<321:19:32,  2.15s/it]
                                                          

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                                      /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (101907408 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                    

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  5%/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  5%|▌         | 31000/569592 [45:54<349:11:49,  2.33s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-31000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-31000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-31000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-31000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-31000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-31000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-30000] due to args.save_total_limit


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  5%|▌         | 31130/569592 [56:15<456:5/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
0:41,  3.05s/it]
                                                          

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       /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (103329614 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                   

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  warnings.warn(
316:57:09,  2.12s/it]
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  warnings.warn(
54:31,  4.09s/it]
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  5%|▌         | 31268//home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  warnings.warn(
6:10,  3.70s/it]
                                                            

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  5%|▌         | 31288/569592 [1:04:02<207:55:55,  1.39s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

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  warnings.warn(
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    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (94374912 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                        

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  warnings.warn(
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  warnings.warn(
,  1.56s/it]
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  6%|▌         | 31408/56959/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
2 [1:09:43<314:30:33,  2.10s/it]
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                                                    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
        

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                                    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                        

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  6%|▌         | 31528/569592 [1:15:27<343:13:06,  2.30s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (89679681 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

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/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                            

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                        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90827016 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                    

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  6%|�/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  warnings.warn(
,  2.90s/it]
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  6%|▌       /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  6%|▌         | 31752/569592 [1:26:27<364:18:33,  2.44s//home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (104175000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
it]
                                                            

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                                                            /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (109455511 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(


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  6%|▌         | 318/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (97421556 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  6%|▌  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (105470981 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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                                /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                            

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  warnings.warn(
.24s/it]
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            /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (119416194 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                

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                                                        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (106739205 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
    

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  6%|▌         | 32000/569592 [1:38:29<284:38:24,  1.91s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-32000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-32000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-32000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-32000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-32000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-32000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-31000] due to args.save_total_limit

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  warnings.warn(
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  6%|�/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
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  6%|▌         | 32083/569592 [1:44:45<690:23:08,  4.62s/it]
                                                            

  6%|▌         | 32083/569592 [1:44:45<690:23:08,  4.62s/it]
  6%|▌         | 32084/569592 [1:44:50<704:07:19,  4.72s/it]
                                                            

  6%|▌         | 32084/569592 [1:44:50<704:07:19,  4.72s/it]
  6%|▌         | 32085/569592 [1:44:53<632:08:29,  4.23s/it]
                                                            

  6%|▌         | 32085/569592 [1:44:53<632:08:29,  4.23s/it]
  6%|▌         | 32086/569592 [1:44:59<688:50:43,  4.61s/it]
                                                            

  6%|▌         | 32086/569592 [1:44:59<688:50:43,  4.61s/it]
  6%|▌         | 32087/569592 [1:45:02<634:40:06,  4.25s/it]
                                                            

  6%|▌         | 32087/569592 [1:45:02<634:40:06,  4.25s/it]
  6%|▌         | 32088/569592 [1:45:03<483:38:24,  3.24s/it]
                                                            

  6%|▌         | 32088/569592 [1:45:03<483:38:24,  3.24s/it]
  6%|▌         | 32089/569592 [1:45:04<379:17:28,  2.54s/it]
                                                            

  6%|▌         | 32089/569592 [1:45:04<379:17:28,  2.54s/it]
  6%|▌         | 32090/569592 [1:45:08<441:30:09,  2.96s/it]
                                                            

  6%|▌         | 32090/569592 [1:45:08<441:30:09,  2.96s/it]
  6%|▌         | 32091/569592 [1:45:09<351:39:59,  2.36s/it]
                                                            

  6%|▌         | 32091/569592 [1:45:09<351:39:59,  2.36s/it]
  6%|▌         | 32092/569592 [1:45:12<417:03:24,  2.79s/it]
                                                            

  6%|▌         | 32092/569592 [1:45:12<417:03:24,  2.79s/it]
  6%|▌         | 32093/569592 [1:45:18<521:17:12,  3.49s/it]
                                                            

  6%|▌         | 32093/569592 [1:45:18<521:17:12,  3.49s/it]
  6%|▌         | 32094/569592 [1:45:21<530:08:39,  3.55s/it]
                                                            

  6%|▌         | 32094/569592 [1:45:21<530:08:39,  3.55s/it]
  6%|▌         | 32095/569592 [1:45:22<410:18:07,  2.75s/it]
                                                            

  6%|▌         | 32095/569592 [1:45:22<410:18:07,  2.75s/it]
  6%|▌         | 32096/569592 [1:45:26<472:34:52,  3.17s/it]
                                                            

  6%|▌         | 32096/569592 [1:45:26<472:34:52,  3.17s/it]
  6%|▌         | 32097/569592 [1:45:27<382:40:41,  2.56s/it]
                                                            

  6%|▌         | 32097/569592 [1:45:27<382:40:41,  2.56s/it]
  6%|▌         | 32098/569592 [1:45:28<309:16:48,  2.07s/it]
                                                            

  6%|▌         | 32098/569592 [1:45:28<309:16:48,  2.07s/it]
  6%|▌         | 32099/569592 [1:45:29<259:11:42,  1.74s/it]
                                                            

  6%|▌         | 32099/569592 [1:45:29<259:11:42,  1.74s/it]
  6%|▌         | 32100/569592 [1:45:33<329:24:56,  2.21s/it]
                                                            

  6%|▌         | 32100/569592 [1:45:33<329:24:56,  2.21s/it]
  6%|▌         | 32101/569592 [1:45:33<272:14:01,  1.82s/it]
                                                            

  6%|▌         | 32101/569592 [1:45:34<272:14:01,  1.82s/it]
  6%|▌         | 32102/569592 [1:45:34<232:27:02,  1.56s/it]
                                                            

  6%|▌         | 32102/569592 [1:45:34<232:27:02,  1.56s/it]
  6%|▌         | 32103/569592 [1:45:38<312:20:58,  2.09s/it]
                                                            

  6%|▌         | 32103/569592 [1:45:38<312:20:58,  2.09s/it]
  6%|▌         | 32104/569592 [1:45:39<261:42:48,  1.75s/it]
                                                            

  6%|▌         | 32104/569592 [1:45:39<261:42:48,  1.75s/it]
  6%|▌         | 32105/569592 [1:45:40<236:09:52,  1.58s/it]
                                                            

  6%|▌         | 32105/569592 [1:45:40<236:09:52,  1.58s/it]
  6%|▌         | 32106/569592 [1:45:45<414:37:15,  2.78s/it]
                                                            

  6%|▌         | 32106/569592 [1:45:45<414:37:15,  2.78s/it]
  6%|▌         | 32107/569592 [1:45:47<339:54:50,  2.28s/it]
                                                            

  6%|▌         | 32107/569592 [1:45:47<339:54:50,  2.28s/it]
  6%|▌         | 32108/569592 [1:45:48<293:39:25,  1.97s/it]
                                                            

  6%|▌         | 32108/569592 [1:45:48<293:39:25,  1.97s/it]
  6%|▌         | 32109/569592 [1:45:50<303:30:09,  2.03s/it]
                                                            

  6%|▌         | 32109/569592 [1:45:50<303:30:09,  2.03s/it]
  6%|▌         | 32110/569592 [1:45:51<267:42:15,  1.79s/it]
                                                            

  6%|▌         | 32110/569592 [1:45:51<267:42:15,  1.79s/it]
  6%|▌         | 32111/569592 [1:45:55<355:43:30,  2.38s/it]
                                                            

  6%|▌         | 32111/569592 [1:45:55<355:43:30,  2.38s/it]
  6%|▌         | 32112/569592 [1:45:59<408:56:26,  2.74s/it]
                                                            

  6%|▌         | 32112/569592 [1:45:59<408:56:26,  2.74s/it]
  6%|▌         | 32113/569592 [1:46:01<401:26:27,  2.69s/it]
                                                            

  6%|▌         | 32113/569592 [1:46:01<401:26:27,  2.69s/it]
  6%|▌         | 32114/569592 [1:46:02<327:05:25,  2.19s/it]
                                                            

  6%|▌         | 32114/569592 [1:46:02<327:05:25,  2.19s/it]
  6%|▌         | 32115/569592 [1:46:05<364:46:25,  2.44s/it]
                                                            

  6%|▌         | 32115/569592 [1:46:05<364:46:25,  2.44s/it]
  6%|▌         | 32116/569592 [1:46:08<394:20:51,  2.64s/it]
                                                            

  6%|▌         | 32116/569592 [1:46:08<394:20:51,  2.64s/it]
  6%|▌         | 32117/569592 [1:46:13<474:27:22,  3.18s/it]
                                                            

  6%|▌         | 32117/569592 [1:46:13<474:27:22,  3.18s/it]
  6%|▌         | 32118/569592 [1:46:14<374:11:39,  2.51s/it]
                                                            

  6%|▌         | 32118/569592 [1:46:14<374:11:39,  2.51s/it]
  6%|▌         | 32119/569592 [1:46:15<318:00:45,  2.13s/it]
                                                            

  6%|▌         | 32119/569592 [1:46:15<318:00:45,  2.13s/it]
  6%|▌         | 32120/569592 [1:46:18<364:04:25,  2.44s/it]
                                                            

  6%|▌         | 32120/569592 [1:46:18<364:04:25,  2.44s/it]
  6%|▌         | 32121/569592 [1:46:22<415:48:13,  2.79s/it]
                                                            

  6%|▌         | 32121/569592 [1:46:22<415:48:13,  2.79s/it]
  6%|▌         | 32122/569592 [1:46:23<337:57:57,  2.26s/it]
                                                            

  6%|▌         | 32122/569592 [1:46:23<337:57:57,  2.26s/it]
  6%|▌         | 32123/569592 [1:46:26<360:10:37,  2.41s/it]
                                                            

  6%|▌         | 32123/569592 [1:46:26<360:10:37,  2.41s/it]
  6%|▌         | 32124/569592 [1:46:27<325:59:06,  2.18s/it]
                                                            

  6%|▌         | 32124/569592 [1:46:27<325:59:06,  2.18s/it]
  6%|▌         | 32125/569592 [1:46:32<438:41:13,  2.94s/it]
                                                            

  6%|▌         | 32125/569592 [1:46:32<438:41:13,  2.94s/it]
  6%|▌         | 32126/569592 [1:46:34<425:31:00,  2.85s/it]
                                                            

  6%|▌         | 32126/569592 [1:46:35<425:31:00,  2.85s/it]
  6%|▌         | 32127/569592 [1:46:36<369:47:34,  2.48s/it]
                                                            

  6%|▌         | 32127/569592 [1:46:36<369:47:34,  2.48s/it]
  6%|▌         | 32128/569592 [1:46:38<348:54:56,  2.34s/it]
                                                            

  6%|▌         | 32128/569592 [1:46:38<348:54:56,  2.34s/it]
  6%|▌         | 32129/569592 [1:46:42<431:32:28,  2.89s/it]
                                                            

  6%|▌         | 32129/569592 [1:46:42<431:32:28,  2.89s/it]
  6%|▌         | 32130/569592 [1:46:44<391:52:51,  2.62s/it]
                                                            

  6%|▌         | 32130/569592 [1:46:44<391:52:51,  2.62s/it]
  6%|▌         | 32131/569592 [1:46:46<359:30:54,  2.41s/it]
                                                            

  6%|▌         | 32131/569592 [1:46:46<359:30:54,  2.41s/it]
  6%|▌         | 32132/569592 [1:46:47<301:06:37,  2.02s/it]
                                                            

  6%|▌         | 32132/569592 [1:46:47<301:06:37,  2.02s/it]
  6%|▌         | 32133/569592 [1:46:53<447:03:35,  2.99s/it]
                                                            

  6%|▌         | 32133/569592 [1:46:53<447:03:35,  2.99s/it]
  6%|▌         | 32134/569592 [1:46:55<402:34:02,  2.70s/it]
                                                            

  6%|▌         | 32134/569592 [1:46:55<402:34:02,  2.70s/it]
  6%|▌         | 32135/569592 [1:46:56<366:10:01,  2.45s/it]
                                                            

  6%|▌         | 32135/569592 [1:46:56<366:10:01,  2.45s/it]
  6%|▌         | 32136/569592 [1:46:59<356:04:00,  2.39s/it]
                                                            

  6%|▌         | 32136/569592 [1:46:59<356:04:00,  2.39s/it]
  6%|▌         | 32137/569592 [1:47:02<418:33:14,  2.80s/it]
                                                            

  6%|▌         | 32137/569592 [1:47:02<418:33:14,  2.80s/it]
  6%|▌         | 32138/569592 [1:47:05<397:20:43,  2.66s/it]
                                                            

  6%|▌         | 32138/569592 [1:47:05<397:20:43,  2.66s/it]
  6%|▌         | 32139/569592 [1:47:07<382:37:31,  2.56s/it]
                                                            

  6%|▌         | 32139/569592 [1:47:07<382:37:31,  2.56s/it]
  6%|▌         | 32140/569592 [1:47:09<343:43:55,  2.30s/it]
                                                            

  6%|▌         | 32140/569592 [1:47:09<343:43:55,  2.30s/it]
  6%|▌         | 32141/569592 [1:47:12<398:17:46,  2.67s/it]
                                                            

  6%|▌         | 32141/569592 [1:47:12<398:17:46,  2.67s/it]
  6%|▌         | 32142/569592 [1:47:15<402:27:18,  2.70s/it]
                                                            

  6%|▌         | 32142/569592 [1:47:15<402:27:18,  2.70s/it]
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  6%|▌         | 32145/569592 [1:47:23<409:12:44,  2.74s/it]
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  6%|▌         | 32147/569592 [1:47:26<343:52:04,  2.30s/it]
  6%|▌         | 32148/569592 [1:47:28<322:37:17,  2.16s/it]
                                                            

  6%|▌         | 32148/569592 [1:47:28<322:37:17,  2.16s/it]
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  6%|▌         | 32149/569592 [1:47:32<409:26:50,  2.74s/it]
  6%|▌         | 32150/569592 [1:47:34<342:47:42,  2.30s/it]
                                                            

  6%|▌         | 32150/569592 [1:47:34<342:47:42,  2.30s/it]
  6%|▌         | 32151/569592 [1:47:36<368:49:33,  2.47s/it]
                                                            

  6%|▌         | 32151/569592 [1:47:36<368:49:33,  2.47s/it]
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  6%|▌         | 32152/569592 [1:47:39<395:41:07,  2.65s/it]
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  6%|▌         | 32153/569592 [1:47:43<452:25:21,  3.03s/it]
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  6%|▌         | 32154/569592 [1:47:45<371:33:06,  2.49s/it]
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  6%|▌         | 32155/569592 [1:47:47<379:51:49,  2.54s/it]
  6%|▌         | 32156/569592 [1:47:50<371:41:06,  2.49s/it]
                                                            

  6%|▌         | 32156/569592 [1:47:50<371:41:06,  2.49s/it]
  6%|▌         | 32157/569592 [1:47:54<435:47:00,  2.92s/it]
                                                            

  6%|▌         | 32157/569592 [1:47:54<435:47:00,  2.92s/it]
  6%|▌         | 32158/569592 [1:47:55<349:08:54,  2.34s/it]
                                                            

  6%|▌         | 32158/569592 [1:47:55<349:08:54,  2.34s/it]
  6%|▌         | 32159/569592 [1:47:57<360:27:14,  2.41s/it]
                                                            

  6%|▌         | 32159/569592 [1:47:57<360:27:14,  2.41s/it]
  6%|▌         | 32160/569592 [1:48:01<411:49:04,  2.76s/it]
                                                            

  6%|▌         | 32160/569592 [1:48:01<411:49:04,  2.76s/it]
  6%|▌         | 32161/569592 [1:48:04<429:15:12,  2.88s/it]
                                                            

  6%|▌         | 32161/569592 [1:48:04<429:15:12,  2.88s/it]
  6%|▌         | 32162/569592 [1:48:05<342:07:52,  2.29s/it]
                                                            

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  6%|▌         | 32164/569592 [1:48:12<460:24:59,  3.08s/it]
                                                            

  6%|▌         | 32164/569592 [1:48:12<460:24:59,  3.08s/it]
  6%|▌         | 32165/569592 [1:48:17<545:02:25,  3.65s/it]
                                                            

  6%|▌         | 32165/569592 [1:48:17<545:02:25,  3.65s/it]
  6%|▌         | 32166/569592 [1:48:21<580:26:08,  3.89s/it]
                                                            

  6%|▌         | 32166/569592 [1:48:21<580:26:08,  3.89s/it]
  6%|▌         | 32167/569592 [1:48:22<445:54:13,  2.99s/it]
                                                            

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  6%|▌         | 32168/569592 [1:48:23<354:20:19,  2.37s/it]
                                                            

  6%|▌         | 32168/569592 [1:48:23<354:20:19,  2.37s/it]
  6%|▌         | 32169/569592 [1:48:24<290:39:51,  1.95s/it]
                                                            

  6%|▌         | 32169/569592 [1:48:24<290:39:51,  1.95s/it]
  6%|▌         | 32170/569592 [1:48:29<426:37:25,  2.86s/it]
                                                            

  6%|▌         | 32170/569592 [1:48:29<426:37:25,  2.86s/it]
  6%|▌         | 32171/569592 [1:48:34<525:36:14,  3.52s/it]
                                                            

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  6%|▌         | 32172/569592 [1:48:40<611:14:50,  4.09s/it]
                                                            

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  6%|▌         | 32174/569592 [1:48:46<549:39:53,  3.68s/it]
                                                            

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  6%|▌         | 32175/569592 [1:48:51<591:57:09,  3.97s/it]
                                                            

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  6%|▌         | 32176/569592 [1:48:52<457:09:20,  3.06s/it]
                                                            

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  6%|▌         | 32177/569592 [1:48:56<498:56:26,  3.34s/it]
                                                            

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  6%|▌         | 32178/569592 [1:48:59<497:32:38,  3.33s/it]
                                                            

  6%|▌         | 32178/569592 [1:48:59<497:32:38,  3.33s/it]
  6%|▌         | 32179/569592 [1:49:02<501:17:04,  3.36s/it]
                                                            

  6%|▌         | 32179/569592 [1:49:02<501:17:04,  3.36s/it]
  6%|▌         | 32180/569592 [1:49:06<524:23:02,  3.51s/it]
                                                            

  6%|▌         | 32180/569592 [1:49:06<524:23:02,  3.51s/it]
  6%|▌         | 32181/569592 [1:49:09<499:29:55,  3.35s/it]
                                                            

  6%|▌         | 32181/569592 [1:49:09<499:29:55,  3.35s/it]
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  6%|▌         | 32185/569592 [1:49:24<530:25:01,  3.55s/it]
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  warnings.warn(
it]
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  warnings.warn(
6<416:23:58,  2.79s/it]
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/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

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                                         /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                   

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                     /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                       

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 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (96000000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                           

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     /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                       

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                                                 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (103946760 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
           

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  6%|▌       /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90816400 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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                                                         /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (94099482 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
   

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  warnings.warn(
<401:40:48,  2.69s/it]
                                                            

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/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90994915 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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                                                 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (102118230 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
           

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                                 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                           

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  warnings.warn(
13:52<659:32:39,  4.42s/it]
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  6%|▌        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90610906 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 | 32698/569592 [2:14:56<370:39:38,  2.49s/it]
                                                            

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                                     /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (91978783 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                       

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  6%|▌         | 32866/569592 [2:23:00<526:48:09,/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (93011016 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
  3.53s/it]
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  6%|▌   /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
      | 32888/569592 [2:24:25<538:46:39,  3.61s/it]
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                                                     /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (105871698 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
       

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  6%|▌         | 33000/569592 [2:29:55<667:17:16,  4.48s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-33000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-33000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-33000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-33000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-33000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-33000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-32000] due to args.save_total_limit

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  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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                    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (105437376 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                        

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                                            /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (93576675 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                

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  warnings.warn(
9592 [2:40:35<382:46:16,  2.57s/it]
                                                            

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                                                /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (96582828 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
            

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  warnings.warn(
,  2.28s/it]
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  6%|▌         | 33305/569592 [2:46:50<337:03:53,  2.26s/it]
                                                            

  6%|▌         | 33305/569592 [2:46:/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
50<337:03:53,  2.26s/it]
  6%|▌         | 33306/569592 [2:46:56<467:02:03,  3.14s/it]
                                                            

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  6%|▌         | 33333/569592 [2:48:21<640:58:05,  4.30s/it]
                                                            

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  6%|▌         | 33370/569592 [2:50:36<426:42:26,  2.86s/it]
                                                            

  6%|▌         | 33370/569592 [2:50:36<426:42:26,  2.86s/it]
  6%|▌         | 33371/569592 [2:50:37<33/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
9:10:25,  2.28s/it]
                                                            

  6%|▌         | 33371/569592 [2:50:37<339:10:25,  2.28s/it]
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  6%|▌         | 33480/569592/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 [2:56:14<488:30:32,  3.28s/it]
                                                            

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  6%|▌         |/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (92152249 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  6%|▌         | 33607/569592 [3:02:50<517:01:43,  3.47s/it]
                                                            

  6%|▌         | 33607/569592 [3:02:50<517:01:43,  3.47s/it]
  6%|▌         | 33608/569592 [3:02:51<402:37:58,  2.70s/it]
                                                            

  6%|▌         | 33608/569592 [3:02:51<402:37:58,  2.70s/it]
  6%|▌         | 33609/569592 [3:02:52<324:26:51,  2.18s/it]
                                                            

  6%|▌         | 33609/569592 [3:02:52<324:26:51,  2.18s/it]
  6%|▌         | 33610/569592 [3:02:57<453:56:28,  3.05s/it]
                                                            

  6%|▌         | 33610/569592 [3:02:57<453:56:28,  3.05s/it]
  6%|▌         | 33611/569592 [3:02:58<364:10:38,  2.45s/it]
                                                            

  6%|▌         | 33611/569592 [3:02:58<364:10:38,  2.45s/it]
  6%|▌         | 33612/569592 [3:03:03<476:29:54,  3.20s/it]
                                                            

  6%|▌         | 33612/569592 [3:03:03<476:29:54,  3.20s/it]
  6%|▌         | 33613/569592 [3:03:04<373:21:31,  2.51s/it]
                                                            

  6%|▌         | 33613/569592 [3:03:04<373:21:31,  2.51s/it]
  6%|▌         | 33614/569592 [3:03:04<303:40:10,  2.04s/it]
                                                            

  6%|▌         | 33614/569592 [3:03:04<303:40:10,  2.04s/it]
  6%|▌         | 33615/569592 [3:03:05<257:19:21,  1.73s/it]
                                                            

  6%|▌         | 33615/569592 [3:03:05<257:19:21,  1.73s/it]
  6%|▌         | 33616/569592 [3:03:11<407:51:09,  2.74s/it]
                                                            

  6%|▌         | 33616/569592 [3:03:11<407:51:09,  2.74s/it]
  6%|▌         | 33617/569592 [3:03:12<328:29:24,  2.21s/it]
                                                            

  6%|▌         | 33617/569592 [3:03:12<328:29:24,  2.21s/it]
  6%|▌         | 33618/569592 [3:03:12<271:09:17,  1.82s/it]
                                                            

  6%|▌         | 33618/569592 [3:03:12<271:09:17,  1.82s/it]
  6%|▌         | 33619/569592 [3:03:16<358:24:24,  2.41s/it]
                                                            

  6%|▌         | 33619/569592 [3:03:16<358:24:24,  2.41s/it]
  6%|▌         | 33620/569592 [3:03:17<294:03:19,  1.98s/it]
                                                            

  6%|▌         | 33620/569592 [3:03:17<294:03:19,  1.98s/it]
  6%|▌         | 33621/569592 [3:03:18<249:04:36,  1.67s/it]
                                                            

  6%|▌         | 33621/569592 [3:03:18<249:04:36,  1.67s/it]
  6%|▌         | 33622/569592 [3:03:19<217:13:18,  1.46s/it]
                                                            

  6%|▌         | 33622/569592 [3:03:19<217:13:18,  1.46s/it]
  6%|▌         | 33623/569592 [3:03:21<228:33:53,  1.54s/it]
                                                            

  6%|▌         | 33623/569592 [3:03:21<228:33:53,  1.54s/it]
  6%|▌         | 33624/569592 [3:03:23<274:38:38,  1.84s/it]
                                                            

  6%|▌         | 33624/569592 [3:03:23<274:38:38,  1.84s/it]
  6%|▌         | 33625/569592 [3:03:28<388:52:02,  2.61s/it]
                                                            

  6%|▌         | 33625/569592 [3:03:28<388:52:02,  2.61s/it]
  6%|▌         | 33626/569592 [3:03:29<314:19:55,  2.11s/it]
                                                            

  6%|▌         | 33626/569592 [3:03:29<314:19:55,  2.11s/it]
  6%|▌         | 33627/569592 [3:03:30<285:29:21,  1.92s/it]
                                                            

  6%|▌         | 33627/569592 [3:03:30<285:29:21,  1.92s/it]
  6%|▌         | 33628/569592 [3:03:34<354:28:39,  2.38s/it]
                                                            

  6%|▌         | 33628/569592 [3:03:34<354:28:39,  2.38s/it]
  6%|▌         | 33629/569592 [3:03:37<380:05:54,  2.55s/it]
                                                            

  6%|▌         | 33629/569592 [3:03:37<380:05:54,  2.55s/it]
  6%|▌         | 33630/569592 [3:03:38<341:18:37,  2.29s/it]
                                                            

  6%|▌         | 33630/569592 [3:03:38<341:18:37,  2.29s/it]
  6%|▌         | 33631/569592 [3:03:42<383:40:21,  2.58s/it]
                                                            

  6%|▌         | 33631/569592 [3:03:42<383:40:21,  2.58s/it]
  6%|▌         | 33632/569592 [3:03:44<393:04:51,  2.64s/it]
                                                            

  6%|▌         | 33632/569592 [3:03:44<393:04:51,  2.64s/it]
  6%|▌         | 33633/569592 [3:03:48<451:57:26,  3.04s/it]
                                                            

  6%|▌         | 33633/569592 [3:03:48<451:57:26,  3.04s/it]
  6%|▌         | 33634/569592 [3:03:49<360:21:41,  2.42s/it]
                                                            

  6%|▌         | 33634/569592 [3:03:49<360:21:41,  2.42s/it]
  6%|▌         | 33635/569592 [3:03:50<299:11:58,  2.01s/it]
                                                            

  6%|▌         | 33635/569592 [3:03:50<299:11:58,  2.01s/it]
  6%|▌         | 33636/569592 [3:03:53<344:57:34,  2.32s/it]
                                                            

  6%|▌         | 33636/569592 [3:03:53<344:57:34,  2.32s/it]
  6%|▌         | 33637/569592 [3:03:58<452:01:34,  3.04s/it]
                                                            

  6%|▌         | 33637/569592 [3:03:58<452:01:34,  3.04s/it]
  6%|▌         | 33638/569592 [3:03:59<359:33:04,  2.42s/it]
                                                            

  6%|▌         | 33638/569592 [3:03:59<359:33:04,  2.42s/it]
  6%|▌         | 33639/569592 [3:04:02<364:01:29,  2.45s/it]
                                                            

  6%|▌         | 33639/569592 [3:04:02<364:01:29,  2.45s/it]
  6%|▌         | 33640/569592 [3:04:06<446:28:29,  3.00s/it]
                                                            

  6%|▌         | 33640/569592 [3:04:06<446:28:29,  3.00s/it]
  6%|▌         | 33641/569592 [3:04:10<482:29:09,  3.24s/it]
                                                            

  6%|▌         | 33641/569592 [3:04:10<482:29:09,  3.24s/it]
  6%|▌         | 33642/569592 [3:04:11<379:29:33,  2.55s/it]
                                                            

  6%|▌         | 33642/569592 [3:04:11<379:29:33,  2.55s/it]
  6%|▌         | 33643/569592 [3:04:12<316:13:20,  2.12s/it]
                                                            

  6%|▌         | 33643/569592 [3:04:12<316:13:20,  2.12s/it]
  6%|▌         | 33644/569592 [3:04:14<317:38:46,  2.13s/it]
                                                            

  6%|▌         | 33644/569592 [3:04:14<317:38:46,  2.13s/it]
  6%|▌         | 33645/569592 [3:04:20<475:50:58,  3.20s/it]
                                                            

  6%|▌         | 33645/569592 [3:04:20<475:50:58,  3.20s/it]
  6%|▌         | 33646/569592 [3:04:21<375:38:43,  2.52s/it]
                                                            

  6%|▌         | 33646/569592 [3:04:21<375:38:43,  2.52s/it]
  6%|▌         | 33647/569592 [3:04:21<305:14:29,  2.05s/it]
                                                            

  6%|▌         | 33647/569592 [3:04:21<305:14:29,  2.05s/it]
  6%|▌         | 33648/569592 [3:04:24<341:13:01,  2.29s/it]
                                                            

  6%|▌         | 33648/569592 [3:04:24<341:13:01,  2.29s/it]
  6%|▌         | 33649/569592 [3:04:30<485:14:07,  3.26s/it]
                                                            

  6%|▌         | 33649/569592 [3:04:30<485:14:07,  3.26s/it]
  6%|▌         | 33650/569592 [3:04:31<382:52:00,  2.57s/it]
                                                            

  6%|▌         | 33650/569592 [3:04:31<382:52:00,  2.57s/it]
  6%|▌         | 33651/569592 [3:04:32<314:44:40,  2.11s/it]
                                                            

  6%|▌         | 33651/569592 [3:04:32<314:44:40,  2.11s/it]
  6%|▌         | 33652/569592 [3:04:35<375:14:22,  2.52s/it]
                                                            

  6%|▌         | 33652/569592 [3:04:35<375:14:22,  2.52s/it]
  6%|▌         | 33653/569592 [3:04:40<465:33:50,  3.13s/it]
                                                            

  6%|▌         | 33653/569592 [3:04:40<465:33:50,  3.13s/it]
  6%|▌         | 33654/569592 [3:04:41<368:03:25,  2.47s/it]
                                                            

  6%|▌         | 33654/569592 [3:04:41<368:03:25,  2.47s/it]
  6%|▌         | 33655/569592 [3:04:44<408:57:28,  2.75s/it]
                                                            

  6%|▌         | 33655/569592 [3:04:44<408:57:28,  2.75s/it]
  6%|▌         | 33656/569592 [3:04:45<328:21:56,  2.21s/it]
                                                            

  6%|▌         | 33656/569592 [3:04:45<328:21:56,  2.21s/it]
  6%|▌         | 33657/569592 [3:04:49<387:31:27,  2.60s/it]
                                                            

  6%|▌         | 33657/569592 [3:04:49<387:31:27,  2.60s/it]
  6%|▌         | 33658/569592 [3:04:50<351:10:33,  2.36s/it]
                                                            

  6%|▌         | 33658/569592 [3:04:50<351:10:33,  2.36s/it]
  6%|▌         | 33659/569592 [3:04:54<396:53:51,  2.67s/it]
                                                            

  6%|▌         | 33659/569592 [3:04:54<396:53:51,  2.67s/it]
  6%|▌         | 33660/569592 [3:04:55<343:56:07,  2.31s/it]
                                                            

  6%|▌         | 33660/569592 [3:04:55<343:56:07,  2.31s/it]
  6%|▌         | 33661/569592 [3:05:00<461:32:14,  3.10s/it]
                                                            

  6%|▌         | 33661/569592 [3:05:00<461:32:14,  3.10s/it]
  6%|▌         | 33662/569592 [3:05:01<364:53:12,  2.45s/it]
                                                            

  6%|▌         | 33662/569592 [3:05:01<364:53:12,  2.45s/it]
  6%|▌         | 33663/569592 [3:05:05<405:57:19,  2.73s/it]
                                                            

  6%|▌         | 33663/569592 [3:05:05<405:57:19,  2.73s/it]
  6%|▌         | 33664/569592 [3:05:10<516:01:57,  3.47s/it]
                                                            

  6%|▌         | 33664/569592 [3:05:10<516:01:57,  3.47s/it]
  6%|▌         | 33665/569592 [3:05:13<504:13:48,  3.39s/it]
                                                            

  6%|▌         | 33665/569592 [3:05:13<504:13:48,  3.39s/it]
  6%|▌         | 33666/569592 [3:05:18<571:22:33,  3.84s/it]
                                                            

  6%|▌         | 33666/569592 [3:05:18<571:22:33,  3.84s/it]
  6%|▌         | 33667/569592 [3:05:19<440:47:30,  2.96s/it]
                                                            

  6%|▌         | 33667/569592 [3:05:19<440:47:30,  2.96s/it]
  6%|▌         | 33668/569592 [3:05:22<462:02:44,  3.10s/it]
                                                            

  6%|▌         | 33668/569592 [3:05:22<462:02:44,  3.10s/it]
  6%|▌         | 33669/569592 [3:05:27<541:04:44,  3.63s/it]
                                                            

  6%|▌         | 33669/569592 [3:05:27<541:04:44,  3.63s/it]
  6%|▌         | 33670/569592 [3:05:30<526:52:42,  3.54s/it]
                                                            

  6%|▌         | 33670/569592 [3:05:30<526:52:42,  3.54s/it]
  6%|▌         | 33671/569592 [3:05:36<609:35:11,  4.09s/it]
                                                            

  6%|▌         | 33671/569592 [3:05:36<609:35:11,  4.09s/it]
  6%|▌         | 33672/569592 [3:05:37<466:31:44,  3.13s/it]
                                                            

  6%|▌         | 33672/569592 [3:05:37<466:31:44,  3.13s/it]
  6%|▌         | 33673/569592 [3:05:38<368:38:49,  2.48s/it]
                                                            

  6%|▌         | 33673/569592 [3:05:38<368:38:49,  2.48s/it]
  6%|▌         | 33674/569592 [3:05:43<477:56:25,  3.21s/it]
                                                            

  6%|▌         | 33674/569592 [3:05:43<477:56:25,  3.21s/it]
  6%|▌         | 33675/569592 [3:05:47<550:49:46,  3.70s/it]
                                                            

  6%|▌         | 33675/569592 [3:05:47<550:49:46,  3.70s/it]
  6%|▌         | 33676/569592 [3:05:48<424:59:59,  2.85s/it]
                                                            

  6%|▌         | 33676/569592 [3:05:48<424:59:59,  2.85s/it]
  6%|▌         | 33677/569592 [3:05:52<457:57:17,  3.08s/it]
                                                            

  6%|▌         | 33677/569592 [3:05:52<457:57:17,  3.08s/it]
  6%|▌         | 33678/569592 [3:05:55<482:20:53,  3.24s/it]
                                                            

  6%|▌         | 33678/569592 [3:05:55<482:20:53,  3.24s/it]
  6%|▌         | 33679/569592 [3:06:00<554:47:01,  3.73s/it]
                                                            

  6%|▌         | 33679/569592 [3:06:00<554:47:01,  3.73s/it]
  6%|▌         | 33680/569592 [3:06:06<619:10:58,  4.16s/it]
                                                            

  6%|▌         | 33680/569592 [3:06:06<619:10:58,  4.16s/it]
  6%|▌         | 33681/569592 [3:06:08<560:52:23,  3.77s/it]
                                                            

  6%|▌         | 33681/569592 [3:06:08<560:52:23,  3.77s/it]
  6%|▌         | 33682/569592 [3:06:13<616:39:41,  4.14s/it]
                                                            

  6%|▌         | 33682/569592 [3:06:13<616:39:41,  4.14s/it]
  6%|▌         | 33683/569592 [3:06:17<581:54:25,  3.91s/it]
                                                            

  6%|▌         | 33683/569592 [3:06:17<581:54:25,  3.91s/it]
  6%|▌         | 33684/569592 [3:06:20<546:47:00,  3.67s/it]
                                                            

  6%|▌         | 33684/569592 [3:06:20<546:47:00,  3.67s/it]
  6%|▌         | 33685/569592 [3:06:24<546:33:20,  3.67s/it]
                                                            

  6%|▌         | 33685/569592 [3:06:24<546:33:20,  3.67s/it]
  6%|▌         | 33686/569592 [3:06:24<424:00:06,  2.85s/it]
                                                            

  6%|▌         | 33686/569592 [3:06:24<424:00:06,  2.85s/it]
  6%|▌         | 33687/569592 [3:06:29<498:00:58,  3.35s/it]
                                                            

  6%|▌         | 33687/569592 [3:06:29<498:00:58,  3.35s/it]
  6%|▌         | 33688/569592 [3:06:34<557:20:56,  3.74s/it]
                                                            

  6%|▌         | 33688/569592 [3:06:34<557:20:56,  3.74s/it]
  6%|▌         | 33689/569592 [3:06:37<546:22:27,  3.67s/it]
                                                            

  6%|▌         | 33689/569592 [3:06:37<546:22:27,  3.67s/it]
  6%|▌         | 33690/569592 [3:06:42<606:59:49,  4.08s/it]
                                                            

  6%|▌         | 33690/569592 [3:06:42<606:59:49,  4.08s/it]
  6%|▌         | 33691/569592 [3:06:45<558:44:06,  3.75s/it]
                                                            

  6%|▌         | 33691/569592 [3:06:45<558:44:06,  3.75s/it]
  6%|▌         | 33692/569592 [3:06:50<595:36:58,  4.00s/it]
                                                            

  6%|▌         | 33692/569592 [3:06:50<595:36:58,  4.00s/it]
  6%|▌         | 33693/569592 [3:06:54<625:32:11,  4.20s/it]
                                                            

  6%|▌         | 33693/569592 [3:06:54<625:32:11,  4.20s/it]
  6%|▌         | 33694/569592 [3:06:55<478:17:08,  3.21s/it]
                                                            

  6%|▌         | 33694/569592 [3:06:55<478:17:08,  3.21s/it]
  6%|▌         | 33695/569592 [3:06:58<475:45:49,  3.20s/it]
                                                            

  6%|▌         | 33695/569592 [3:06:58<475:45:49,  3.20s/it]
  6%|▌         | 33696/569592 [3:06:59<373:10:50,  2.51s/it]
                                                            

  6%|▌         | 33696/569592 [3:06:59<373:10:50,  2.51s/it]
  6%|▌         | 33697/569592 [3:07:03<407:42:19,  2.74s/it]
                                                            

  6%|▌         | 33697/569592 [3:07:03<407:42:19,  2.74s/it]
  6%|▌         | 33698/569592 [3:07:08<504:12:51,  3.39s/it]
                                                            

  6%|▌         | 33698/569592 [3:07:08<504:12:51,  3.39s/it]
  6%|▌         | 33699/569592 [3:07:13<582:47:55,  3.92s/it]
                                                            

  6%|▌         | 33699/569592 [3:07:13<582:47:55,  3.92s/it]
  6%|▌         | 33700/569592 [3:07:17<606:59:59,  4.08s/it]
                                                            

  6%|▌         | 33700/569592 [3:07:17<606:59:59,  4.08s/it]
  6%|▌         | 33701/569592 [3:07:20<564:44:58,  3.79s/it]
                                                            

  6%|▌         | 33701/569592 [3:07:20<564:44:58,  3.79s/it]
  6%|▌         | 33702/569592 [3:07:25<615:46:07,  4.14s/it]
                                                            

  6%|▌         | 33702/569592 [3:07:25<615:46:07,  4.14s/it]
  6%|▌         | 33703/569592 [3:07:30<643:10:21,  4.32s/it]
                                                            

  6%|▌         | 33703/569592 [3:07:30<643:10:21,  4.32s/it]
  6%|▌         | 33704/569592 [3:07:35<670:36:11,  4.50s/it]
                                                            

  6%|▌         | 33704/569592 [3:07:35<670:36:11,  4.50s/it]
  6%|▌         | 33705/569592 [3:07:39<672:11:34,  4.52s/it]
                                                            

  6%|▌         | 33705/569592 [3:07:39<672:11:34,  4.52s/it]
  6%|▌         | 33706/569592 [3:07:44<694:15:10,  4.66s/it]
                                                            

  6%|▌         | 33706/569592 [3:07:44<694:15:10,  4.66s/it]
  6%|▌         | 33707/569592 [3:07:48<625:47:04,  4.20s/it]
                                                            

  6%|▌         | 33707/569592 [3:07:48<625:47:04,  4.20s/it]
  6%|▌         | 33708/569592 [3:07:51<575:39:20,  3.87s/it]
                                                            

  6%|▌         | 33708/569592 [3:07:51<575:39:20,  3.87s/it]
  6%|▌         | 33709/569592 [3:07:54<545:47:34,  3.67s/it]
                                                            

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                                                    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (94970766 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
        

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  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98911692 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
27s/it]
                                                            

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                                    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                        

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  6%|▌         | 33810/569592 [3:12:44<575:47:25,  3.87s/it]
  6%|▌         | 33811/569592 [3:12:47<537:19:24,  3.61s/it]
                                                            

  6%|▌         | 33811/569592 [3:12:47<537:19:24,  3.61s/it]
  6%|▌         | 33812/569592 [3:12:47<415:54:24,  2.79s/it]
                                                            

  6%|▌         | 33812/569592 [3:12:47<415:54:24,  2.79s/it]
  6%|▌         | 33813/569592 [3:12:51<461:06:24,  3.10s/it]
                                                            

  6%|▌         | 33813/569592 [3:12:51<461:06:24,  3.10s/it]
  6%|▌         | 33814/569592 [3:12:56<534:53:46,  3.59s/it]
                                                            

  6%|▌         | 33814/569592 [3:12:56<534:53:46,  3.59s/it]
  6%|▌         | 33815/569592 [3:13:01<600:59:48,  4.04s/it]
                                                            

  6%|▌         | 33815/569592 [3:13:01<600:59:48,  4.04s/it]
  6%|▌         | 33816/569592 [3:13:05<585:38:41,  3.94s/it]
                                                            

  6%|▌         | 33816/569592 [3:13:05<585:38:41,  3.94s/it]
  6%|▌         | 33817/569592 [3:13:10<635:18:29,  4.27s/it]
                                                            

  6%|▌         | 33817/569592 [3:13:10<635:18:29,  4.27s/it]
  6%|▌         | 33818/569592 [3:13:13<582:36:17,  3.91s/it]
                                                            

  6%|▌         | 33818/569592 [3:13:13<582:36:17,  3.91s/it]
  6%|▌         | 33819/569592 [3:13:16<561:22:39,  3.77s/it]
                                                            

  6%|▌         | 33819/569592 [3:13:16<561:22:39,  3.77s/it]
  6%|▌         | 33820/569592 [3:13:19<528:21:14,  3.55s/it]
                                                            

  6%|▌         | 33820/569592 [3:13:19<528:21:14,  3.55s/it]
  6%|▌         | 33821/569592 [3:13:24<582:22:22,  3.91s/it]
                                                            

  6%|▌         | 33821/569592 [3:13:24<582:22:22,  3.91s/it]
  6%|▌         | 33822/569592 [3:13:28<563:47:55,  3.79s/it]
                                                            

  6%|▌         | 33822/569592 [3:13:28<563:47:55,  3.79s/it]
  6%|▌         | 33823/569592 [3:13:32<602:39:10,  4.05s/it]
                                                            

  6%|▌         | 33823/569592 [3:13:32<602:39:10,  4.05s/it]
  6%|▌         | 33824/569592 [3:13:37<630:28:30,  4.24s/it]
                                                            

  6%|▌         | 33824/569592 [3:13:37<630:28:30,  4.24s/it]
  6%|▌         | 33825/569592 [3:13:40<577:11:55,  3.88s/it]
                                                            

  6%|▌         | 33825/569592 [3:13:40<577:11:55,  3.88s/it]
  6%|▌         | 33826/569592 [3:13:44<567:03:33,  3.81s/it]
                                                            

  6%|▌         | 33826/569592 [3:13:44<567:03:33,  3.81s/it]
  6%|▌         | 33827/569592 [3:13:47<544:38:34,  3.66s/it]
                                                            

  6%|▌         | 33827/569592 [3:13:47<544:38:34,  3.66s/it]
  6%|▌         | 33828/569592 [3:13:50<522:49:35,  3.51s/it]
                                                            

  6%|▌         | 33828/569592 [3:13:50<522:49:35,  3.51s/it]
  6%|▌         | 33829/569592 [3:13:51<406:59:10,  2.73s/it]
                                                            

  6%|▌         | 33829/569592 [3:13:51<406:59:10,  2.73s/it]
  6%|▌         | 33830/569592 [3:13:56<505:40:52,  3.40s/it]
                                                            

  6%|▌         | 33830/569592 [3:13:56<505:40:52,  3.40s/it]
  6%|▌         | 33831/569592 [3:13:57<394:41:45,  2.65s/it]
                                                            

  6%|▌         | 33831/569592 [3:13:57<394:41:45,  2.65s/it]
  6%|▌         | 33832/569592 [3:13:58<319:34:57,  2.15s/it]
                                                            

  6%|▌         | 33832/569592 [3:13:58<319:34:57,  2.15s/it]
  6%|▌         | 33833/569592 [3:14:02<385:48:34,  2.59s/it]
                                                            

  6%|▌         | 33833/569592 [3:14:02<385:48:34,  2.59s/it]
  6%|▌         | 33834/569592 [3:14:02<312:06:26,  2.10s/it]
                                                            

  6%|▌         | 33834/569592 [3:14:03<312:06:26,  2.10s/it]
  6%|▌         | 33835/569592 [3:14:08<472:36:36,  3.18s/it]
                                                            

  6%|▌         | 33835/569592 [3:14:08<472:36:36,  3.18s/it]
  6%|▌         | 33836/569592 [3:14:12<481:19:58,  3.23s/it]
                                                            

  6%|▌         | 33836/569592 [3:14:12<481:19:58,  3.23s/it]
  6%|▌         | 33837/569592 [3:14:15<492:18:13,  3.31s/it]
                                                            

  6%|▌         | 33837/569592 [3:14:15<492:18:13,  3.31s/it]
  6%|▌         | 33838/569592 [3:14:16<386:42:54,  2.60s/it]
                                                            

  6%|▌         | 33838/569592 [3:14:16<386:42:54,  2.60s/it]
  6%|▌         | 33839/569592 [3:14:17<312:59:43,  2.10s/it]
                                                            

  6%|▌         | 33839/569592 [3:14:17<312:59:43,  2.10s/it]
  6%|▌         | 33840/569592 [3:14:18<261:16:06,  1.76s/it]
                                                            

  6%|▌         | 33840/569592 [3:14:18<261:16:06,  1.76s/it]
  6%|▌         | 33841/569592 [3:14:21<331:43:42,  2.23s/it]
                                                            

  6%|▌         | 33841/569592 [3:14:21<331:43:42,  2.23s/it]
  6%|▌         | 33842/569592 [3:14:22<275:00:28,  1.85s/it]
                                                            

  6%|▌         | 33842/569592 [3:14:22<275:00:28,  1.85s/it]
  6%|▌         | 33843/569592 [3:14:25<341:05:58,  2.29s/it]
                                                            

  6%|▌         | 33843/569592 [3:14:25<341:05:58,  2.29s/it]
  6%|▌         | 33844/569592 [3:14:26<282:16:28,  1.90s/it]
                                                            

  6%|▌         | 33844/569592 [3:14:26<282:16:28,  1.90s/it]
  6%|▌         | 33845/569592 [3:14:27<243:20:59,  1.64s/it]
                                                            

  6%|▌         | 33845/569592 [3:14:27<243:20:59,  1.64s/it]
  6%|▌         | 33846/569592 [3:14:29<244:56:41,  1.65s/it]
                                                            

  6%|▌         | 33846/569592 [3:14:29<244:56:41,  1.65s/it]
  6%|▌         | 33847/569592 [3:14:33<339:52:21,  2.28s/it]
                                                            

  6%|▌         | 33847/569592 [3:14:33<339:52:21,  2.28s/it]
  6%|▌         | 33848/569592 [3:14:34<279:26:37,  1.88s/it]
                                                            

  6%|▌         | 33848/569592 [3:14:34<279:26:37,  1.88s/it]
  6%|▌         | 33849/569592 [3:14:38<374:35:47,  2.52s/it]
                                                            

  6%|▌         | 33849/569592 [3:14:38<374:35:47,  2.52s/it]
  6%|▌         | 33850/569592 [3:14:39<318:56:27,  2.14s/it]
                                                            

  6%|▌         | 33850/569592 [3:14:39<318:56:27,  2.14s/it]
  6%|▌         | 33851/569592 [3:14:40<270:37:03,  1.82s/it]
                                                            

  6%|▌         | 33851/569592 [3:14:40<270:37:03,  1.82s/it]
  6%|▌         | 33852/569592 [3:14:43<337:03:40,  2.26s/it]
                                                            

  6%|▌         | 33852/569592 [3:14:44<337:03:40,  2.26s/it]
  6%|▌         | 33853/569592 [3:14:45<298:05:56,  2.00s/it]
                                                            

  6%|▌         | 33853/569592 [3:14:45<298:05:56,  2.00s/it]
  6%|▌         | 33854/569592 [3:14:49<412:08:51,  2.77s/it]
                                                            

  6%|▌         | 33854/569592 [3:14:49<412:08:51,  2.77s/it]
  6%|▌         | 33855/569592 [3:14:51<344:30:18,  2.31s/it]
                                                            

  6%|▌         | 33855/569592 [3:14:51<344:30:18,  2.31s/it]
  6%|▌         | 33856/569592 [3:14:52<293:06:14,  1.97s/it]
                                                            

  6%|▌         | 33856/569592 [3:14:52<293:06:14,  1.97s/it]
  6%|▌         | 33857/569592 [3:14:55<350:15:22,  2.35s/it]
                                                            

  6%|▌         | 33857/569592 [3:14:55<350:15:22,  2.35s/it]
  6%|▌         | 33858/569592 [3:14:59<434:21:25,  2.92s/it]
                                                            

  6%|▌         | 33858/569592 [3:14:59<434:21:25,  2.92s/it]
  6%|▌         | 33859/569592 [3:15:01<366:35:13,  2.46s/it]
                                                            

  6%|▌         | 33859/569592 [3:15:01<366:35:13,  2.46s/it]
  6%|▌         | 33860/569592 [3:15:02<298:47:33,  2.01s/it]
                                                            

  6%|▌         | 33860/569592 [3:15:02<298:47:33,  2.01s/it]
  6%|▌         | 33861/569592 [3:15:05<370:28:15,  2.49s/it]
                                                            

  6%|▌         | 33861/569592 [3:15:05<370:28:15,  2.49s/it]
  6%|▌         | 33862/569592 [3:15:09<443:07:30,  2.98s/it]
                                                            

  6%|▌         | 33862/569592 [3:15:09<443:07:30,  2.98s/it]
  6%|▌         | 33863/569592 [3:15:11<392:20:25,  2.64s/it]
                                                            

  6%|▌         | 33863/569592 [3:15:11<392:20:25,  2.64s/it]
  6%|▌         | 33864/569592 [3:15:12<316:31:43,  2.13s/it]
                                                            

  6%|▌         | 33864/569592 [3:15:12<316:31:43,  2.13s/it]
  6%|▌         | 33865/569592 [3:15:15<367:50:34,  2.47s/it]
                                                            

  6%|▌         | 33865/569592 [3:15:15<367:50:34,  2.47s/it]
  6%|▌         | 33866/569592 [3:15:20<441:45:36,  2.97s/it]
                                                            

  6%|▌         | 33866/569592 [3:15:20<441:45:36,  2.97s/it]
  6%|▌         | 33867/569592 [3:15:21<373:47:38,  2.51s/it]
                                                            

  6%|▌         | 33867/569592 [3:15:21<373:47:38,  2.51s/it]
  6%|▌         | 33868/569592 [3:15:22<304:34:08,  2.05s/it]
                                                            

  6%|▌         | 33868/569592 [3:15:22<304:34:08,  2.05s/it]
  6%|▌         | 33869/569592 [3:15:26<374:35:23,  2.52s/it]
                                                            

  6%|▌         | 33869/569592 [3:15:26<374:35:23,  2.52s/it]
  6%|▌         | 33870/569592 [3:15:30<473:30:34,  3.18s/it]
                                                            

  6%|▌         | 33870/569592 [3:15:30<473:30:34,  3.18s/it]
  6%|▌         | 33871/569592 [3:15:32<382:34:04,  2.57s/it]
                                                            

  6%|▌         | 33871/569592 [3:15:32<382:34:04,  2.57s/it]
  6%|▌         | 33872/569592 [3:15:32<309:15:10,  2.08s/it]
                                                            

  6%|▌         | 33872/569592 [3:15:32<309:15:10,  2.08s/it]
  6%|▌         | 33873/569592 [3:15:36<374:55:03,  2.52s/it]
                                                            

  6%|▌         | 33873/569592 [3:15:36<374:55:03,  2.52s/it]
  6%|▌         | 33874/569592 [3:15:40<461:17:05,  3.10s/it]
                                                            

  6%|▌         | 33874/569592 [3:15:40<461:17:05,  3.10s/it]
  6%|▌         | 33875/569592 [3:15:42<371:34:02,  2.50s/it]
                                                            

  6%|▌         | 33875/569592 [3:15:42<371:34:02,  2.50s/it]
  6%|▌         | 33876/569592 [3:15:45<421:34:38,  2.83s/it]
                                                            

  6%|▌         | 33876/569592 [3:15:45<421:34:38,  2.83s/it]
  6%|▌         | 33877/569592 [3:15:46<339:28:11,  2.28s/it]
                                                            

  6%|▌         | 33877/569592 [3:15:46<339:28:11,  2.28s/it]
  6%|▌         | 33878/569592 [3:15:52<486:27:53,  3.27s/it]
                                                            

  6%|▌         | 33878/569592 [3:15:52<486:27:53,  3.27s/it]
  6%|▌         | 33879/569592 [3:15:53<412:29:46,  2.77s/it]
                                                            

  6%|▌         | 33879/569592 [3:15:53<412:29:46,  2.77s/it]
  6%|▌         | 33880/569592 [3:15:54<330:42:22,  2.22s/it]
                                                            

  6%|▌         | 33880/569592 [3:15:54<330:42:22,  2.22s/it]
  6%|▌         | 33881/569592 [3:15:58<400:01:48,  2.69s/it]
                                                            

  6%|▌         | 33881/569592 [3:15:58<400:01:48,  2.69s/it]
  6%|▌         | 33882/569592 [3:16:01<397:52:15,  2.67s/it]
                                                            

  6%|▌         | 33882/569592 [3:16:01<397:52:15,  2.67s/it]
  6%|▌         | 33883/569592 [3:16:04<431:45:40,  2.90s/it]
                                                            

  6%|▌         | 33883/569592 [3:16:04<431:45:40,  2.90s/it]
  6%|▌         | 33884/569592 [3:16:05<346:33:45,  2.33s/it]
                                                            

  6%|▌         | 33884/569592 [3:16:05<346:33:45,  2.33s/it]
  6%|▌         | 33885/569592 [3:16:06<285:25:48,  1.92s/it]
                                                            

  6%|▌         | 33885/569592 [3:16:06<285:25:48,  1.92s/it]
  6%|▌         | 33886/569592 [3:16:10<383:17:49,  2.58s/it]
                                                            

  6%|▌         | 33886/569592 [3:16:10<383:17:49,  2.58s/it]
  6%|▌         | 33887/569592 [3:16:13<394:43:23,  2.65s/it]
                                                            

  6%|▌         | 33887/569592 [3:16:13<394:43:23,  2.65s/it]
  6%|▌         | 33888/569592 [3:16:14<320:13:11,  2.15s/it]
                                                            

  6%|▌         | 33888/569592 [3:16:14<320:13:11,  2.15s/it]
  6%|▌         | 33889/569592 [3:16:16<328:47:03,  2.21s/it]
                                                            

  6%|▌         | 33889/569592 [3:16:16<328:47:03,  2.21s/it]
  6%|▌         | 33890/569592 [3:16:21<460:01:29,  3.09s/it]
                                                            

  6%|▌         | 33890/569592 [3:16:22<460:01:29,  3.09s/it]
  6%|▌         | 33891/569592 [3:16:25<484:05:16,  3.25s/it]
                                                            

  6%|▌         | 33891/569592 [3:16:25<484:05:16,  3.25s/it]
  6%|▌         | 33892/569592 [3:16:26<382:04:06,  2.57s/it]
                                                            

  6%|▌         | 33892/569592 [3:16:26<382:04:06,  2.57s/it]
  6%|▌         | 33893/569592 [3:16:29<414:05:08,  2.78s/it]
                                                            

  6%|▌         | 33893/569592 [3:16:29<414:05:08,  2.78s/it]
  6%|▌         | 33894/569592 [3:16:35<532:03:53,  3.58s/it]
                                                            

  6%|▌         | 33894/569592 [3:16:35<532:03:53,  3.58s/it]
  6%|▌         | 33895/569592 [3:16:36<415:49:35,  2.79s/it]
                                                            

  6%|▌         | 33895/569592 [3:16:36<415:49:35,  2.79s/it]
  6%|▌         | 33896/569592 [3:16:39<442:52:57,  2.98s/it]
                                                            

  6%|▌         | 33896/569592 [3:16:39<442:52:57,  2.98s/it]
  6%|▌         | 33897/569592 [3:16:43<482:48:55,  3.24s/it]
                                                            

  6%|▌         | 33897/569592 [3:16:43<482:48:55,  3.24s/it]
  6%|▌         | 33898/569592 [3:16:46<487:34:22,  3.28s/it]
                                                            

  6%|▌         | 33898/569592 [3:16:46<487:34:22,  3.28s/it]
  6%|▌         | 33899/569592 [3:16:47<383:46:17,  2.58s/it]
                                                            

  6%|▌         | 33899/569592 [3:16:47<383:46:17,  2.58s/it]
  6%|▌         | 33900/569592 [3:16:52<488:28:42,  3.28s/it]
                                                            

  6%|▌         | 33900/569592 [3:16:52<488:28:42,  3.28s/it]
  6%|▌         | 33901/569592 [3:16:56<489:21:34,  3.29s/it]
                                                            

  6%|▌         | 33901/569592 [3:16:56<489:21:34,  3.29s/it]
  6%|▌         | 33902/569592 [3:17:00<554:45:25,  3.73s/it]
                                                            

  6%|▌         | 33902/569592 [3:17:00<554:45:25,  3.73s/it]
  6%|▌         | 33903/569592 [3:17:03<528:29:39,  3.55s/it]
                                                            

  6%|▌         | 33903/569592 [3:17:03<528:29:39,  3.55s/it]
  6%|▌         | 33904/569592 [3:17:08<579:33:49,  3.89s/it]
                                                            

  6%|▌         | 33904/569592 [3:17:08<579:33:49,  3.89s/it]
  6%|▌         | 33905/569592 [3:17:11<547:56:12,  3.68s/it]
                                                            

  6%|▌         | 33905/569592 [3:17:11<547:56:12,  3.68s/it]
  6%|▌         | 33906/569592 [3:17:14<519:30:16,  3.49s/it]
                                                            

  6%|▌         | 33906/569592 [3:17:14<519:30:16,  3.49s/it]
  6%|▌         | 33907/569592 [3:17:19<580:09:52,  3.90s/it]
                                                            

  6%|▌         | 33907/569592 [3:17:19<580:09:52,  3.90s/it]
  6%|▌         | 33908/569592 [3:17:23<580:00:27,  3.90s/it]
                                                            

  6%|▌         | 33908/569592 [3:17:23<580:00:27,  3.90s/it]
  6%|▌         | 33909/569592 [3:17:26<553:34:19,  3.72s/it]
                                                            

  6%|▌         | 33909/569592 [3:17:26<553:34:19,  3.72s/it]
  6%|▌         | 33910/569592 [3:17:31<610:19:10,  4.10s/it]
                                                            

  6%|▌         | 33910/569592 [3:17:31<610:19:10,  4.10s/it]
  6%|▌         | 33911/569592 [3:17:35<584:15:32,  3.93s/it]
                                                            

  6%|▌         | 33911/569592 [3:17:35<584:15:32,  3.93s/it]
  6%|▌         | 33912/569592 [3:17:38<563:11:10,  3.78s/it]
                                                            

  6%|▌         | 33912/569592 [3:17:38<563:11:10,  3.78s/it]
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        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (103201856 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                    

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  6%|▌         | 34000/569592 [3:22:08<412:29:43,  2.77s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-34000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-34000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-34000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-34000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-34000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-34000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-33000] due to args.save_total_limit

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  6%|▌         | 34012/569592 [3:24:48<677:31:35,  4.55s/it]
  6%|▌         | 34013/569592 [3:24:48<515:09:57,  3.46s/it]
                                                            

  6%|▌         | 34013/569592 [3:24:48<515:09:57,  3.46s/it]
  6%|▌         | 34014/569592 [3:24:49<401:24:29,  2.70s/it]
                                                            

  6%|▌         | 34014/569592 [3:24:49<401:24:29,  2.70s/it]
  6%|▌         | 34015/569592 [3:24:54<473:51:54,  3.19s/it]
                                                            

  6%|▌         | 34015/569592 [3:24:54<473:51:54,  3.19s/it]
  6%|▌         | 34016/569592 [3:24:59<586:59:47,  3.95s/it]
                                                            

  6%|▌         | 34016/569592 [3:24:59<586:59:47,  3.95s/it]
  6%|▌         | 34017/569592 [3:25:04<606:52:22,  4.08s/it]
                                                            

  6%|▌         | 34017/569592 [3:25:04<606:52:22,  4.08s/it]
  6%|▌         | 34018/569592 [3:25:07<588:53:51,  3.96s/it]
                                                            

  6%|▌         | 34018/569592 [3:25:07<588:53:51,  3.96s/it]
  6%|▌         | 34019/569592 [3:25:08<452:29:10,  3.04s/it]
                                                            

  6%|▌         | 34019/569592 [3:25:08<452:29:10,  3.04s/it]
  6%|▌         | 34020/569592 [3:25:12<493:45:51,  3.32s/it]
                                                            

  6%|▌         | 34020/569592 [3:25:12<493:45:51,  3.32s/it]
  6%|▌         | 34021/569592 [3:25:17<563:37:49,  3.79s/it]
                                                            

  6%|▌         | 34021/569592 [3:25:17<563:37:49,  3.79s/it]
  6%|▌         | 34022/569592 [3:25:21<560:11:36,  3.77s/it]
                                                            

  6%|▌         | 34022/569592 [3:25:21<560:11:36,  3.77s/it]
  6%|▌         | 34023/569592 [3:25:26<595:56:44,  4.01s/it]
                                                            

  6%|▌         | 34023/569592 [3:25:26<595:56:44,  4.01s/it]
  6%|▌         | 34024/569592 [3:25:30<624:20:54,  4.20s/it]
                                                            

  6%|▌         | 34024/569592 [3:25:30<624:20:54,  4.20s/it]
  6%|▌         | 34025/569592 [3:25:34<601:13:36,  4.04s/it]
                                                            

  6%|▌         | 34025/569592 [3:25:34<601:13:36,  4.04s/it]
  6%|▌         | 34026/569592 [3:25:39<630:54:53,  4.24s/it]
                                                            

  6%|▌         | 34026/569592 [3:25:39<630:54:53,  4.24s/it]
  6%|▌         | 34027/569592 [3:25:39<481:59:36,  3.24s/it]
                                                            

  6%|▌         | 34027/569592 [3:25:39<481:59:36,  3.24s/it]
  6%|▌         | 34028/569592 [3:25:40<384:08:01,  2.58s/it]
                                                            

  6%|▌         | 34028/569592 [3:25:40<384:08:01,  2.58s/it]
  6%|▌         | 34029/569592 [3:25:44<439:50:46,  2.96s/it]
                                                            

  6%|▌         | 34029/569592 [3:25:44<439:50:46,  2.96s/it]
  6%|▌         | 34030/569592 [3:25:48<463:25:13,  3.12s/it]
                                                            

  6%|▌         | 34030/569592 [3:25:48<463:25:13,  3.12s/it]
  6%|▌         | 34031/569592 [3:25:53<537:15:37,  3.61s/it]
                                                            

  6%|▌         | 34031/569592 [3:25:53<537:15:37,  3.61s/it]
  6%|▌         | 34032/569592 [3:25:57<585:34:47,  3.94s/it]
                                                            

  6%|▌         | 34032/569592 [3:25:57<585:34:47,  3.94s/it]
  6%|▌         | 34033/569592 [3:26:02<616:58:48,  4.15s/it]
                                                            

  6%|▌         | 34033/569592 [3:26:02<616:58:48,  4.15s/it]
  6%|▌         | 34034/569592 [3:26:06<632:11:12,  4.25s/it]
                                                            

  6%|▌         | 34034/569592 [3:26:06<632:11:12,  4.25s/it]
  6%|▌         | 34035/569592 [3:26:11<663:25:03,  4.46s/it]
                                                            

  6%|▌         | 34035/569592 [3:26:11<663:25:03,  4.46s/it]
  6%|▌         | 34036/569592 [3:26:12<504:58:51,  3.39s/it]
                                                            

  6%|▌         | 34036/569592 [3:26:12<504:58:51,  3.39s/it]
  6%|▌         | 34037/569592 [3:26:15<493:10:46,  3.32s/it]
                                                            

  6%|▌         | 34037/569592 [3:26:15<493:10:46,  3.32s/it]
  6%|▌         | 34038/569592 [3:26:20<533:33:00,  3.59s/it]
                                                            

  6%|▌         | 34038/569592 [3:26:20<533:33:00,  3.59s/it]
  6%|▌         | 34039/569592 [3:26:24<587:14:43,  3.95s/it]
                                                            

  6%|▌         | 34039/569592 [3:26:24<587:14:43,  3.95s/it]
  6%|▌         | 34040/569592 [3:26:30<650:53:39,  4.38s/it]
                                                            

  6%|▌         | 34040/569592 [3:26:30<650:53:39,  4.38s/it]
  6%|▌         | 34041/569592 [3:26:34<631:39:02,  4.25s/it]
                                                            

  6%|▌         | 34041/569592 [3:26:34<631:39:02,  4.25s/it]
  6%|▌         | 34042/569592 [3:26:38<614:41:12,  4.13s/it]
                                                            

  6%|▌         | 34042/569592 [3:26:38<614:41:12,  4.13s/it]
  6%|▌         | 34043/569592 [3:26:42<635:40:39,  4.27s/it]
                                                            

  6%|▌         | 34043/569592 [3:26:42<635:40:39,  4.27s/it]
  6%|▌         | 34044/569592 [3:26:47<650:19:15,  4.37s/it]
                                                            

  6%|▌         | 34044/569592 [3:26:47<650:19:15,  4.37s/it]
  6%|▌         | 34045/569592 [3:26:50<601:08:47,  4.04s/it]
                                                            

  6%|▌         | 34045/569592 [3:26:50<601:08:47,  4.04s/it]
  6%|▌         | 34046/569592 [3:26:54<576:40:56,  3.88s/it]
                                                            

  6%|▌         | 34046/569592 [3:26:54<576:40:56,  3.88s/it]
  6%|▌         | 34047/569592 [3:26:57<567:32:23,  3.82s/it]
                                                            

  6%|▌         | 34047/569592 [3:26:57<567:32:23,  3.82s/it]
  6%|▌         | 34048/569592 [3:26:58<438:25:50,  2.95s/it]
                                                            

  6%|▌         | 34048/569592 [3:26:58<438:25:50,  2.95s/it]
  6%|▌         | 34049/569592 [3:27:03<541:05:24,  3.64s/it]
                                                            

  6%|▌         | 34049/569592 [3:27:03<541:05:24,  3.64s/it]
  6%|▌         | 34050/569592 [3:27:07<535:01:40,  3.60s/it]
                                                            

  6%|▌         | 34050/569592 [3:27:07<535:01:40,  3.60s/it]
  6%|▌         | 34051/569592 [3:27:11<545:36:59,  3.67s/it]
                                                            

  6%|▌         | 34051/569592 [3:27:11<545:36:59,  3.67s/it]
  6%|▌         | 34052/569592 [3:27:16<618:48:57,  4.16s/it]
                                                            

  6%|▌         | 34052/569592 [3:27:16<618:48:57,  4.16s/it]
  6%|▌         | 34053/569592 [3:27:20<596:02:04,  4.01s/it]
                                                            

  6%|▌         | 34053/569592 [3:27:20<596:02:04,  4.01s/it]
  6%|▌         | 34054/569592 [3:27:23<572:58:19,  3.85s/it]
                                                            

  6%|▌         | 34054/569592 [3:27:23<572:58:19,  3.85s/it]
  6%|▌         | 34055/569592 [3:27:26<540:34:45,  3.63s/it]
                                                            

  6%|▌         | 34055/569592 [3:27:26<540:34:45,  3.63s/it]
  6%|▌         | 34056/569592 [3:27:31<602:53:06,  4.05s/it]
                                                            

  6%|▌         | 34056/569592 [3:27:31<602:53:06,  4.05s/it]
  6%|▌         | 34057/569592 [3:27:35<602:50:38,  4.05s/it]
                                                            

  6%|▌         | 34057/569592 [3:27:35<602:50:38,  4.05s/it]
  6%|▌         | 34058/569592 [3:27:40<632:54:52,  4.25s/it]
                                                            

  6%|▌         | 34058/569592 [3:27:40<632:54:52,  4.25s/it]
  6%|▌         | 34059/569592 [3:27:47<752:19:29,  5.06s/it]
                                                            

  6%|▌         | 34059/569592 [3:27:47<752:19:29,  5.06s/it]
  6%|▌         | 34060/569592 [3:27:51<694:02:33,  4.67s/it]
                                                            

  6%|▌         | 34060/569592 [3:27:51<694:02:33,  4.67s/it]
  6%|▌         | 34061/569592 [3:27:56<714:55:23,  4.81s/it]
                                                            

  6%|▌         | 34061/569592 [3:27:56<714:55:23,  4.81s/it]
  6%|▌         | 34062/569592 [3:28:00<691:26:27,  4.65s/it]
                                                            

  6%|▌         | 34062/569592 [3:28:00<691:26:27,  4.65s/it]
  6%|▌         | 34063/569592 [3:28:04<646:19:06,  4.34s/it]
                                                            

  6%|▌         | 34063/569592 [3:28:04<646:19:06,  4.34s/it]
  6%|▌         | 34064/569592 [3:28:05<491:51:00,  3.31s/it]
                                                            

  6%|▌         | 34064/569592 [3:28:05<491:51:00,  3.31s/it]
  6%|▌         | 34065/569592 [3:28:08<496:44:32,  3.34s/it]
                                                            

  6%|▌         | 34065/569592 [3:28:08<496:44:32,  3.34s/it]
  6%|▌         | 34066/569592 [3:28:09<391:22:59,  2.63s/it]
                                                            

  6%|▌         | 34066/569592 [3:28:09<391:22:59,  2.63s/it]
  6%|▌         | 34067/569592 [3:28:14<471:12:29,  3.17s/it]
                                                            

  6%|▌         | 34067/569592 [3:28:14<471:12:29,  3.17s/it]
  6%|▌         | 34068/569592 [3:28:18<533:48:05,  3.59s/it]
                                                            

  6%|▌         | 34068/569592 [3:28:18<533:48:05,  3.59s/it]
  6%|▌         | 34069/569592 [3:28:22<525:32:43,  3.53s/it]
                                                            

  6%|▌         | 34069/569592 [3:28:22<525:32:43,  3.53s/it]
  6%|▌         | 34070/569592 [3:28:22<408:05:33,  2.74s/it]
                                                            

  6%|▌         | 34070/569592 [3:28:22<408:05:33,  2.74s/it]
  6%|▌         | 34071/569592 [3:28:23<332:10:34,  2.23s/it]
                                                            

  6%|▌         | 34071/569592 [3:28:23<332:10:34,  2.23s/it]
  6%|▌         | 34072/569592 [3:28:24<276:14:34,  1.86s/it]
                                                            

  6%|▌         | 34072/569592 [3:28:24<276:14:34,  1.86s/it]
  6%|▌         | 34073/569592 [3:28:29<383:37:52,  2.58s/it]
                                                            

  6%|▌         | 34073/569592 [3:28:29<383:37:52,  2.58s/it]
  6%|▌         | 34074/569592 [3:28:30<317:42:51,  2.14s/it]
                                                            

  6%|▌         | 34074/569592 [3:28:30<317:42:51,  2.14s/it]
  6%|▌         | 34075/569592 [3:28:31<268:39:09,  1.81s/it]
                                                            

  6%|▌         | 34075/569592 [3:28:31<268:39:09,  1.81s/it]
  6%|▌         | 34076/569592 [3:28:35<379:19:01,  2.55s/it]
                                                            

  6%|▌         | 34076/569592 [3:28:35<379:19:01,  2.55s/it]
  6%|▌         | 34077/569592 [3:28:36<307:35:38,  2.07s/it]
                                                            

  6%|▌         | 34077/569592 [3:28:36<307:35:38,  2.07s/it]
  6%|▌         | 34078/569592 [3:28:37<258:16:19,  1.74s/it]
                                                            

  6%|▌         | 34078/569592 [3:28:37<258:16:19,  1.74s/it]
  6%|▌         | 34079/569592 [3:28:38<222:25:59,  1.50s/it]
                                                            

  6%|▌         | 34079/569592 [3:28:38<222:25:59,  1.50s/it]
  6%|▌         | 34080/569592 [3:28:42<348:58:08,  2.35s/it]
                                                            

  6%|▌         | 34080/569592 [3:28:42<348:58:08,  2.35s/it]
  6%|▌         | 34081/569592 [3:28:43<292:45:00,  1.97s/it]
                                                            

  6%|▌         | 34081/569592 [3:28:43<292:45:00,  1.97s/it]
  6%|▌         | 34082/569592 [3:28:45<295:23:17,  1.99s/it]
                                                            

  6%|▌         | 34082/569592 [3:28:45<295:23:17,  1.99s/it]
  6%|▌         | 34083/569592 [3:28:46<251:54:37,  1.69s/it]
                                                            

  6%|▌         | 34083/569592 [3:28:46<251:54:37,  1.69s/it]
  6%|▌         | 34084/569592 [3:28:50<345:20:29,  2.32s/it]
                                                            

  6%|▌         | 34084/569592 [3:28:50<345:20:29,  2.32s/it]
  6%|▌         | 34085/569592 [3:28:52<308:35:15,  2.07s/it]
                                                            

  6%|▌         | 34085/569592 [3:28:52<308:35:15,  2.07s/it]
  6%|▌         | 34086/569592 [3:28:56<387:52:35,  2.61s/it]
                                                            

  6%|▌         | 34086/569592 [3:28:56<387:52:35,  2.61s/it]
  6%|▌         | 34087/569592 [3:28:56<314:02:29,  2.11s/it]
                                                            

  6%|▌         | 34087/569592 [3:28:57<314:02:29,  2.11s/it]
  6%|▌         | 34088/569592 [3:28:58<265:21:48,  1.78s/it]
                                                            

  6%|▌         | 34088/569592 [3:28:58<265:21:48,  1.78s/it]
  6%|▌         | 34089/569592 [3:29:02<375:37:14,  2.53s/it]
                                                            

  6%|▌         | 34089/569592 [3:29:02<375:37:14,  2.53s/it]
  6%|▌         | 34090/569592 [3:29:06<461:21:10,  3.10s/it]
                                                            

  6%|▌         | 34090/569592 [3:29:06<461:21:10,  3.10s/it]
  6%|▌         | 34091/569592 [3:29:07<367:11:08,  2.47s/it]
                                                            

  6%|▌         | 34091/569592 [3:29:07<367:11:08,  2.47s/it]
  6%|▌         | 34092/569592 [3:29:08<300:52:55,  2.02s/it]
                                                            

  6%|▌         | 34092/569592 [3:29:08<300:52:55,  2.02s/it]
  6%|▌         | 34093/569592 [3:29:12<393:28:35,  2.65s/it]
                                                            

  6%|▌         | 34093/569592 [3:29:12<393:28:35,  2.65s/it]
  6%|▌         | 34094/569592 [3:29:16<449:57:03,  3.02s/it]
                                                            

  6%|▌         | 34094/569592 [3:29:16<449:57:03,  3.02s/it]
  6%|▌         | 34095/569592 [3:29:18<387:04:29,  2.60s/it]
                                                            

  6%|▌         | 34095/569592 [3:29:18<387:04:29,  2.60s/it]
  6%|▌         | 34096/569592 [3:29:19<326:39:45,  2.20s/it]
                                                            

  6%|▌         | 34096/569592 [3:29:19<326:39:45,  2.20s/it]
  6%|▌         | 34097/569592 [3:29:25<477:32:41,  3.21s/it]
                                                            

  6%|▌         | 34097/569592 [3:29:25<477:32:41,  3.21s/it]
  6%|▌         | 34098/569592 [3:29:27<430:16:52,  2.89s/it]
                                                            

  6%|▌         | 34098/569592 [3:29:27<430:16:52,  2.89s/it]
  6%|▌         | 34099/569592 [3:29:28<373:42:53,  2.51s/it]
                                                            

  6%|▌         | 34099/569592 [3:29:28<373:42:53,  2.51s/it]
  6%|▌         | 34100/569592 [3:29:29<303:59:46,  2.04s/it]
                                                            

  6%|▌         | 34100/569592 [3:29:30<303:59:46,  2.04s/it]
  6%|▌         | 34101/569592 [3:29:35<446:31:14,  3.00s/it]
                                                            

  6%|▌         | 34101/569592 [3:29:35<446:31:14,  3.00s/it]
  6%|▌         | 34102/569592 [3:29:37<404:09:02,  2.72s/it]
                                                            

  6%|▌         | 34102/569592 [3:29:37<404:09:02,  2.72s/it]
  6%|▌         | 34103/569592 [3:29:40<416:39:41,  2.80s/it]
                                                            

  6%|▌         | 34103/569592 [3:29:40<416:39:41,  2.80s/it]
  6%|▌         | 34104/569592 [3:29:41<334:51:32,  2.25s/it]
                                                            

  6%|▌         | 34104/569592 [3:29:41<334:51:32,  2.25s/it]
  6%|▌         | 34105/569592 [3:29:45<427:20:06,  2.87s/it]
                                                            

  6%|▌         | 34105/569592 [3:29:45<427:20:06,  2.87s/it]
  6%|▌         | 34106/569592 [3:29:47<385:34:14,  2.59s/it]
                                                            

  6%|▌         | 34106/569592 [3:29:47<385:34:14,  2.59s/it]
  6%|▌         | 34107/569592 [3:29:49<369:46:45,  2.49s/it]
                                                            

  6%|▌         | 34107/569592 [3:29:49<369:46:45,  2.49s/it]
  6%|▌         | 34108/569592 [3:29:50<301:03:00,  2.02s/it]
                                                            

  6%|▌         | 34108/569592 [3:29:50<301:03:00,  2.02s/it]
  6%|▌         | 34109/569592 [3:29:56<470:37:49,  3.16s/it]
                                                            

  6%|▌         | 34109/569592 [3:29:56<470:37:49,  3.16s/it]
  6%|▌         | 34110/569592 [3:29:58<433:39:39,  2.92s/it]
                                                            

  6%|▌         | 34110/569592 [3:29:58<433:39:39,  2.92s/it]
  6%|▌         | 34111/569592 [3:30:02<471:46:22,  3.17s/it]
                                                            

  6%|▌         | 34111/569592 [3:30:02<471:46:22,  3.17s/it]
  6%|▌         | 34112/569592 [3:30:06<502:19:52,  3.38s/it]
                                                            

  6%|▌         | 34112/569592 [3:30:06<502:19:52,  3.38s/it]
  6%|▌         | 34113/569592 [3:30:07<394:15:45,  2.65s/it]
                                                            

  6%|▌         | 34113/569592 [3:30:07<394:15:45,  2.65s/it]
  6%|▌         | 34114/569592 [3:30:08<349:01:40,  2.35s/it]
                                                            

  6%|▌         | 34114/569592 [3:30:08<349:01:40,  2.35s/it]
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  6%|▌   /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (91469169 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
1s/it]
                                                            

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                                                         /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90750000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
   

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                                     /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (94099482 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                       

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  6%|▌         | 34284/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98397717 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/569592 [3:39:17<620:30:37,  4.17s/it]
                                                            

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  6%|▌         | 34354/569592 [3:42:17<434:50:09,/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (97363596 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
  2.92s/it]
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  6%|▌         | 34403/569592 [3:45:10<525:59:58,  3./home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
54s/it]
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             /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (94099482 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                               

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  warnings.warn(
t]
                                                            

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  6%|▌         | 34482/569592 [3:48:51<425:26:33,  2.86s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

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                    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98911692 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                        

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                        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (92198400 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                    

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  6%|▌         | 34557/569592 [3:52:51<323:30:39,  2.18s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (108000000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

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  warnings.warn(
6:27,  2.95s/it]
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  6%|▌         | 34628/569592 [3:56:34<391:56:09,  2.64s/it]
                                                            

  6%|▌         | 34628/5/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
69592 [3:56:34<391:56:09,  2.64s/it]
  6%|▌         | 34629/569592 [3:56:38<416:31:12,  2.80s/it]
                                                            

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  6%|▌         | 34633/569592 [3:56:52<502:39:27,  3.38s/it]
  6%|▌         | 34634/569592 [3:56:55<487:33/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (106292300 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
:11,  3.28s/it]
                                                            

  6%|▌         | 34634/569592 [3:56:55<487:33:11,  3.28s/it]
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  6%|▌         | 34661/569592 [3:58:00<358:03:51,  2.41s/it]
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  6%|▌         | 34775/569592 [4:03:/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90750000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
43<220:20:34,  1.48s/it]
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  6%|▌         |/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  warnings.warn(
8<393:32:12,  2.65s/it]
                                                            

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  warnings.warn(
97:27:36,  3.35s/it]
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  6%|▌         | 34884/5/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (103470514 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  6%|�/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100534400 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  6%|▌         | 34931/569592 [4:11:13<314:44:56,  2.12s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

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  warnings.warn(
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                        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100663296 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                    

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  6%|▌         | 35000/569592 [4:15:04<432:47:08,  2.91s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-35000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-35000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-35000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-35000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-35000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-35000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-34000] due to args.save_total_limit

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  6/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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                                             /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (104594490 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
               

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  6%|▌         | 35154/569592 [4:24:30<473:24:45,  3.19s/it]
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  6%|▌         | 35156/569592 [4:24:34<425:59:11,  2.87s/it]
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  6%|▌         | 35157/569592 [4:24:40<531:55:43,  3.58s/it]
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  6%|▌         | 35216/569592 [4:27:48<326:40:21,  2.20s/it]
                                                            

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  6%|▌         | 35217/569592 [4:27:52<397:33:54,  2.68s/it]
                                                            

  6%|▌         | 35217/569592 [4:27:52<397:33:54,  2.68s/it]
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  6%|▌         | 35255/569592 [4:29:22<363:08:43,  2.45s/it]
                                                            

  6%|▌         | 35255/569592 [4:29:22<363:08:43,  2.45s/it]
  6%|▌         | 35256/569592 [4:29:25<358:36:30,  2.42s/it]
                                                            

  6%|▌         | 35256/569592 [4:29:25<35/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
8:36:30,  2.42s/it]
  6%|▌         | 35257/569592 [4:29:26<305:36:14,  2.06s/it]
                                                            

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  6%|▌         | 35305/569592 [4:31:49<495:44:47,  3.34s/it]
                                                            

  6%|▌         | 35305/569592 [4:31:49<495:44/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
:47,  3.34s/it]
  6%|▌         | 35306/569592 [4:31:54<562:53:50,  3.79s/it]
                                                            

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  6%|�/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
�         | 35327/569592 [4:33:12<534:25:25,  3.60s/it]
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  warnings.warn(
  1.91s/it]
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  warnings.warn(
95s/it]
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/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (106003780 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  6%|�/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
�         | 35583/569592 [4:45:11<393:03:00,  2.65s/it]
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  6%|▌         | 35589/569/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
592 [4:45:26<383:45:07,  2.59s/it]
                                                            

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  6%|▋    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (107124888 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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                                 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                           

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  6%|▋       /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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                     /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                       

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  6%|▋         | 35785/569592 [4:55:13<595/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98345472 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
:52:45,  4.02s/it]
                                                            

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  6%|�/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100578090 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  warnings.warn(
it]
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  6%|▋         | 36000/569592 [5:05:19<468:18:06,  3.16s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-36000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-36000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-36000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-36000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-36000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-36000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-35000] due to args.save_total_limit

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  6%|▋         | 360/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (92493545 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
77/569592 [5:11:13<327:22:07,  2.21s/it]
                                                            

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   /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98911692 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                         

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  6%|▋         | 36138/569592 [5:14:27<559:54:57,  3.78s/it]
                                                            

  6%|▋         | 36138/569592 [5:14:27<559:54:57,  3.78s/it]
  6%|▋         | 36139/569592 [5:14:31<549:04:20,  3.71s/it]
                                                            

  6%|▋         | 36139/569592 [5:14:31<549:04:20,  3.71s/it]
  6%|▋         | 36140/569592 [5:14:32<424:32:26,  2.87s/it]
                                                            

  6%|▋         | 36140/569592 [5:14:32<424:32:26,  2.87s/it]
  6%|▋         | 36141/569592 [5:14:33<338:52:10,  2.29s/it]
                                                            

  6%|▋         | 36141/569592 [5:14:33<338:52:10,  2.29s/it]
  6%|▋         | 36142/569592 [5:14:36<387:42:12,  2.62s/it]
                                                            

  6%|▋         | 36142/569592 [5:14:36<387:42:12,  2.62s/it]
  6%|▋         | 36143/569592 [5:14:40<425:32:20,  2.87s/it]
                                                            

  6%|▋         | 36143/569592 [5:14:40<425:32:20,  2.87s/it]
  6%|▋         | 36144/569592 [5:14:43<472:31:14,  3.19s/it]
                                                            

  6%|▋         | 36144/569592 [5:14:44<472:31:14,  3.19s/it]
  6%|▋         | 36145/569592 [5:14:48<536:44:20,  3.62s/it]
                                                            

  6%|▋         | 36145/569592 [5:14:48<536:44:20,  3.62s/it]
  6%|▋         | 36146/569592 [5:14:52<531:06:15,  3.58s/it]
                                                            

  6%|▋         | 36146/569592 [5:14:52<531:06:15,  3.58s/it]
  6%|▋         | 36147/569592 [5:14:53<411:37:09,  2.78s/it]
                                                            

  6%|▋         | 36147/569592 [5:14:53<411:37:09,  2.78s/it]
  6%|▋         | 36148/569592 [5:14:53<328:19:44,  2.22s/it]
                                                            

  6%|▋         | 36148/569592 [5:14:53<328:19:44,  2.22s/it]
  6%|▋         | 36149/569592 [5:14:54<272:14:36,  1.84s/it]
                                                            

  6%|▋         | 36149/569592 [5:14:54<272:14:36,  1.84s/it]
  6%|▋         | 36150/569592 [5:14:55<232:47:31,  1.57s/it]
                                                            

  6%|▋         | 36150/569592 [5:14:55<232:47:31,  1.57s/it]
  6%|▋         | 36151/569592 [5:14:59<316:15:43,  2.13s/it]
                                                            

  6%|▋         | 36151/569592 [5:14:59<316:15:43,  2.13s/it]
  6%|▋         | 36152/569592 [5:15:00<262:01:42,  1.77s/it]
                                                            

  6%|▋         | 36152/569592 [5:15:00<262:01:42,  1.77s/it]
  6%|▋         | 36153/569592 [5:15:05<418:32:58,  2.82s/it]
                                                            

  6%|▋         | 36153/569592 [5:15:05<418:32:58,  2.82s/it]
  6%|▋         | 36154/569592 [5:15:09<462:51:01,  3.12s/it]
                                                            

  6%|▋         | 36154/569592 [5:15:09<462:51:01,  3.12s/it]
  6%|▋         | 36155/569592 [5:15:10<368:28:31,  2.49s/it]
                                                            

  6%|▋         | 36155/569592 [5:15:10<368:28:31,  2.49s/it]
  6%|▋         | 36156/569592 [5:15:13<408:01:47,  2.75s/it]
                                                            

  6%|▋         | 36156/569592 [5:15:13<408:01:47,  2.75s/it]
  6%|▋         | 36157/569592 [5:15:16<432:35:27,  2.92s/it]
                                                            

  6%|▋         | 36157/569592 [5:15:17<432:35:27,  2.92s/it]
  6%|▋         | 36158/569592 [5:15:20<475:21:43,  3.21s/it]
                                                            

  6%|▋         | 36158/569592 [5:15:20<475:21:43,  3.21s/it]
  6%|▋         | 36159/569592 [5:15:21<375:27:50,  2.53s/it]
                                                            

  6%|▋         | 36159/569592 [5:15:21<375:27:50,  2.53s/it]
  6%|▋         | 36160/569592 [5:15:22<305:37:49,  2.06s/it]
                                                            

  6%|▋         | 36160/569592 [5:15:22<305:37:49,  2.06s/it]
  6%|▋         | 36161/569592 [5:15:23<259:15:22,  1.75s/it]
                                                            

  6%|▋         | 36161/569592 [5:15:23<259:15:22,  1.75s/it]
  6%|▋         | 36162/569592 [5:15:27<346:25:53,  2.34s/it]
                                                            

  6%|▋         | 36162/569592 [5:15:27<346:25:53,  2.34s/it]
  6%|▋         | 36163/569592 [5:15:28<284:30:05,  1.92s/it]
                                                            

  6%|▋         | 36163/569592 [5:15:28<284:30:05,  1.92s/it]
  6%|▋         | 36164/569592 [5:15:29<241:00:43,  1.63s/it]
                                                            

  6%|▋         | 36164/569592 [5:15:29<241:00:43,  1.63s/it]
  6%|▋         | 36165/569592 [5:15:32<317:40:22,  2.14s/it]
                                                            

  6%|▋         | 36165/569592 [5:15:32<317:40:22,  2.14s/it]
  6%|▋         | 36166/569592 [5:15:36<369:58:22,  2.50s/it]
                                                            

  6%|▋         | 36166/569592 [5:15:36<369:58:22,  2.50s/it]
  6%|▋         | 36167/569592 [5:15:37<300:36:40,  2.03s/it]
                                                            

  6%|▋         | 36167/569592 [5:15:37<300:36:40,  2.03s/it]
  6%|▋         | 36168/569592 [5:15:37<253:15:27,  1.71s/it]
                                                            

  6%|▋         | 36168/569592 [5:15:38<253:15:27,  1.71s/it]
  6%|▋         | 36169/569592 [5:15:38<218:16:52,  1.47s/it]
                                                            

  6%|▋         | 36169/569592 [5:15:38<218:16:52,  1.47s/it]
  6%|▋         | 36170/569592 [5:15:41<272:39:03,  1.84s/it]
                                                            

  6%|▋         | 36170/569592 [5:15:41<272:39:03,  1.84s/it]
  6%|▋         | 36171/569592 [5:15:47<435:56:55,  2.94s/it]
                                                            

  6%|▋         | 36171/569592 [5:15:47<435:56:55,  2.94s/it]
  6%|▋         | 36172/569592 [5:15:50<454:28:49,  3.07s/it]
                                                            

  6%|▋         | 36172/569592 [5:15:50<454:28:49,  3.07s/it]
  6%|▋         | 36173/569592 [5:15:51<363:49:18,  2.46s/it]
                                                            

  6%|▋         | 36173/569592 [5:15:51<363:49:18,  2.46s/it]
  6%|▋         | 36174/569592 [5:15:52<298:49:29,  2.02s/it]
                                                            

  6%|▋         | 36174/569592 [5:15:52<298:49:29,  2.02s/it]
  6%|▋         | 36175/569592 [5:15:56<383:28:06,  2.59s/it]
                                                            

  6%|▋         | 36175/569592 [5:15:56<383:28:06,  2.59s/it]
  6%|▋         | 36176/569592 [5:15:57<320:31:29,  2.16s/it]
                                                            

  6%|▋         | 36176/569592 [5:15:57<320:31:29,  2.16s/it]
  6%|▋         | 36177/569592 [5:15:59<313:40:37,  2.12s/it]
                                                            

  6%|▋         | 36177/569592 [5:15:59<313:40:37,  2.12s/it]
  6%|▋         | 36178/569592 [5:16:03<381:13:34,  2.57s/it]
                                                            

  6%|▋         | 36178/569592 [5:16:03<381:13:34,  2.57s/it]
  6%|▋         | 36179/569592 [5:16:06<414:02:01,  2.79s/it]
                                                            

  6%|▋         | 36179/569592 [5:16:06<414:02:01,  2.79s/it]
  6%|▋         | 36180/569592 [5:16:07<332:51:05,  2.25s/it]
                                                            

  6%|▋         | 36180/569592 [5:16:07<332:51:05,  2.25s/it]
  6%|▋         | 36181/569592 [5:16:11<407:16:04,  2.75s/it]
                                                            

  6%|▋         | 36181/569592 [5:16:11<407:16:04,  2.75s/it]
  6%|▋         | 36182/569592 [5:16:13<390:19:26,  2.63s/it]
                                                            

  6%|▋         | 36182/569592 [5:16:13<390:19:26,  2.63s/it]
  6%|▋         | 36183/569592 [5:16:17<442:46:35,  2.99s/it]
                                                            

  6%|▋         | 36183/569592 [5:16:17<442:46:35,  2.99s/it]
  6%|▋         | 36184/569592 [5:16:19<374:51:25,  2.53s/it]
                                                            

  6%|▋         | 36184/569592 [5:16:19<374:51:25,  2.53s/it]
  6%|▋         | 36185/569592 [5:16:20<306:37:19,  2.07s/it]
                                                            

  6%|▋         | 36185/569592 [5:16:20<306:37:19,  2.07s/it]
  6%|▋         | 36186/569592 [5:16:24<394:09:17,  2.66s/it]
                                                            

  6%|▋         | 36186/569592 [5:16:24<394:09:17,  2.66s/it]
  6%|▋         | 36187/569592 [5:16:27<431:56:11,  2.92s/it]
                                                            

  6%|▋         | 36187/569592 [5:16:27<431:56:11,  2.92s/it]
  6%|▋         | 36188/569592 [5:16:29<396:46:01,  2.68s/it]
                                                            

  6%|▋         | 36188/569592 [5:16:29<396:46:01,  2.68s/it]
  6%|▋         | 36189/569592 [5:16:30<321:15:06,  2.17s/it]
                                                            

  6%|▋         | 36189/569592 [5:16:30<321:15:06,  2.17s/it]
  6%|▋         | 36190/569592 [5:16:34<399:56:51,  2.70s/it]
                                                            

  6%|▋         | 36190/569592 [5:16:34<399:56:51,  2.70s/it]
  6%|▋         | 36191/569592 [5:16:37<422:03:22,  2.85s/it]
                                                            

  6%|▋         | 36191/569592 [5:16:37<422:03:22,  2.85s/it]
  6%|▋         | 36192/569592 [5:16:43<524:47:52,  3.54s/it]
                                                            

  6%|▋         | 36192/569592 [5:16:43<524:47:52,  3.54s/it]
  6%|▋         | 36193/569592 [5:16:46<542:06:27,  3.66s/it]
                                                            

  6%|▋         | 36193/569592 [5:16:46<542:06:27,  3.66s/it]
  6%|▋         | 36194/569592 [5:16:50<531:05:31,  3.58s/it]
                                                            

  6%|▋         | 36194/569592 [5:16:50<531:05:31,  3.58s/it]
  6%|▋         | 36195/569592 [5:16:51<412:14:13,  2.78s/it]
                                                            

  6%|▋         | 36195/569592 [5:16:51<412:14:13,  2.78s/it]
  6%|▋         | 36196/569592 [5:16:52<330:23:48,  2.23s/it]
                                                            

  6%|▋         | 36196/569592 [5:16:52<330:23:48,  2.23s/it]
  6%|▋         | 36197/569592 [5:16:56<402:45:12,  2.72s/it]
                                                            

  6%|▋         | 36197/569592 [5:16:56<402:45:12,  2.72s/it]
  6%|▋         | 36198/569592 [5:16:57<331:08:01,  2.23s/it]
                                                            

  6%|▋         | 36198/569592 [5:16:57<331:08:01,  2.23s/it]
  6%|▋         | 36199/569592 [5:16:58<273:23:38,  1.85s/it]
                                                            

  6%|▋         | 36199/569592 [5:16:58<273:23:38,  1.85s/it]
  6%|▋         | 36200/569592 [5:17:01<363:16:23,  2.45s/it]
                                                            

  6%|▋         | 36200/569592 [5:17:01<363:16:23,  2.45s/it]
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  6%|▋         | 36201/569592 [5:17:06<453:12:17,  3.06s/it]
  6%|▋         | 36202/569592 [5:17:10<492:19:00,  3.32s/it]
                                                            

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  6%|▋         | 36203/569592 [5:17:13<490:07:19,  3.31s/it]
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  6%|▋         | 36204/569592 [5:17:14<383:00:17,  2.59s/it]
  6%|▋         | 36205/569592 [5:17:17<413:43:42,  2.79s/it]
                                                            

  6%|▋         | 36205/569592 [5:17:17<413:43:42,  2.79s/it]
  6%|▋         | 36206/569592 [5:17:21<450:09:45,  3.04s/it]
                                                            

  6%|▋         | 36206/569592 [5:17:21<450:09:45,  3.04s/it]
  6%|▋         | 36207/569592 [5:17:24<464:23:26,  3.13s/it]
                                                            

  6%|▋         | 36207/569592 [5:17:24<464:23:26,  3.13s/it]
  6%|▋         | 36208/569592 [5:17:25<367:22:51,  2.48s/it]
                                                            

  6%|▋         | 36208/569592 [5:17:25<367:22:51,  2.48s/it]
  6%|▋         | 36209/569592 [5:17:29<404:34:23,  2.73s/it]
                                                            

  6%|▋         | 36209/569592 [5:17:29<404:34:23,  2.73s/it]
  6%|▋         | 36210/569592 [5:17:32<428:36:52,  2.89s/it]
                                                            

  6%|▋         | 36210/569592 [5:17:32<428:36:52,  2.89s/it]
  6%|▋         | 36211/569592 [5:17:35<456:47:19,  3.08s/it]
                                                            

  6%|▋         | 36211/569592 [5:17:35<456:47:19,  3.08s/it]
  6%|▋         | 36212/569592 [5:17:39<463:32:22,  3.13s/it]
                                                            

  6%|▋         | 36212/569592 [5:17:39<463:32:22,  3.13s/it]
  6%|▋         | 36213/569592 [5:17:42<488:30:09,  3.30s/it]
                                                            

  6%|▋         | 36213/569592 [5:17:42<488:30:09,  3.30s/it]
  6%|▋         | 36214/569592 [5:17:46<497:51:47,  3.36s/it]
                                                            

  6%|▋         | 36214/569592 [5:17:46<497:51:47,  3.36s/it]
  6%|▋         | 36215/569592 [5:17:50<530:06:31,  3.58s/it]
                                                            

  6%|▋         | 36215/569592 [5:17:50<530:06:31,  3.58s/it]
  6%|▋         | 36216/569592 [5:17:55<585:26:58,  3.95s/it]
                                                            

  6%|▋         | 36216/569592 [5:17:55<585:26:58,  3.95s/it]
  6%|▋         | 36217/569592 [5:17:58<546:58:13,  3.69s/it]
                                                            

  6%|▋         | 36217/569592 [5:17:58<546:58:13,  3.69s/it]
  6%|▋         | 36218/569592 [5:18:02<556:38:26,  3.76s/it]
                                                            

  6%|▋         | 36218/569592 [5:18:02<556:38:26,  3.76s/it]
  6%|▋         | 36219/569592 [5:18:03<429:43:01,  2.90s/it]
                                                            

  6%|▋         | 36219/569592 [5:18:03<429:43:01,  2.90s/it]
  6%|▋         | 36220/569592 [5:18:04<342:02:22,  2.31s/it]
                                                            

  6%|▋         | 36220/569592 [5:18:04<342:02:22,  2.31s/it]
  6%|▋         | 36221/569592 [5:18:09<467:25:06,  3.15s/it]
                                                            

  6%|▋         | 36221/569592 [5:18:09<467:25:06,  3.15s/it]
  6%|▋         | 36222/569592 [5:18:12<475:22:29,  3.21s/it]
                                                            

  6%|▋         | 36222/569592 [5:18:12<475:22:29,  3.21s/it]
  6%|▋         | 36223/569592 [5:18:15<475:10:51,  3.21s/it]
                                                            

  6%|▋         | 36223/569592 [5:18:15<475:10:51,  3.21s/it]
  6%|▋         | 36224/569592 [5:18:18<471:49:25,  3.18s/it]
                                                            

  6%|▋         | 36224/569592 [5:18:18<471:49:25,  3.18s/it]
  6%|▋         | 36225/569592 [5:18:19<370:15:16,  2.50s/it]
                                                            

  6%|▋         | 36225/569592 [5:18:19<370:15:16,  2.50s/it]
  6%|▋         | 36226/569592 [5:18:23<430:58:10,  2.91s/it]
                                                            

  6%|▋         | 36226/569592 [5:18:23<430:58:10,  2.91s/it]
  6%|▋         | 36227/569592 [5:18:26<442:48:41,  2.99s/it]
                                                            

  6%|▋         | 36227/569592 [5:18:26<442:48:41,  2.99s/it]
  6%|▋         | 36228/569592 [5:18:32<569:32:01,  3.84s/it]
                                                            

  6%|▋         | 36228/569592 [5:18:32<569:32:01,  3.84s/it]
  6%|▋         | 36229/569592 [5:18:35<535:51:52,  3.62s/it]
                                                            

  6%|▋         | 36229/569592 [5:18:35<535:51:52,  3.62s/it]
  6%|▋         | 36230/569592 [5:18:38<505:47:12,  3.41s/it]
                                                            

  6%|▋         | 36230/569592 [5:18:38<505:47:12,  3.41s/it]
  6%|▋         | 36231/569592 [5:18:39<394:45:53,  2.66s/it]
                                                            

  6%|▋         | 36231/569592 [5:18:39<394:45:53,  2.66s/it]
  6%|▋         | 36232/569592 [5:18:43<457:39:46,  3.09s/it]
                                                            

  6%|▋         | 36232/569592 [5:18:43<457:39:46,  3.09s/it]
  6%|▋         | 36233/569592 [5:18:47<475:35:36,  3.21s/it]
                                                            

  6%|▋         | 36233/569592 [5:18:47<475:35:36,  3.21s/it]
  6%|▋         | 36234/569592 [5:18:50<490:21:43,  3.31s/it]
                                                            

  6%|▋         | 36234/569592 [5:18:50<490:21:43,  3.31s/it]
  6%|▋         | 36235/569592 [5:18:55<550:45:38,  3.72s/it]
                                                            

  6%|▋         | 36235/569592 [5:18:55<550:45:38,  3.72s/it]
  6%|▋         | 36236/569592 [5:18:58<526:16:26,  3.55s/it]
                                                            

  6%|▋         | 36236/569592 [5:18:58<526:16:26,  3.55s/it]
  6%|▋         | 36237/569592 [5:18:59<408:17:44,  2.76s/it]
                                                            

  6%|▋         | 36237/569592 [5:18:59<408:17:44,  2.76s/it]
  6%|▋         | 36238/569592 [5:19:03<448:47:53,  3.03s/it]
                                                            

  6%|▋         | 36238/569592 [5:19:03<448:47:53,  3.03s/it]
  6%|▋         | 36239/569592 [5:19:07<490:54:26,  3.31s/it]
                                                            

  6%|▋         | 36239/569592 [5:19:07<490:54:26,  3.31s/it]
  6%|▋         | 36240/569592 [5:19:10<493:27:46,  3.33s/it]
                                                            

  6%|▋         | 36240/569592 [5:19:10<493:27:46,  3.33s/it]
  6%|▋         | 36241/569592 [5:19:13<494:35:53,  3.34s/it]
                                                            

  6%|▋         | 36241/569592 [5:19:13<494:35:53,  3.34s/it]
  6%|▋         | 36242/569592 [5:19:18<558:52:23,  3.77s/it]
                                                            

  6%|▋         | 36242/569592 [5:19:18<558:52:23,  3.77s/it]
  6%|▋         | 36243/569592 [5:19:23<598:52:11,  4.04s/it]
                                                            

  6%|▋         | 36243/569592 [5:19:23<598:52:11,  4.04s/it]
  6%|▋         | 36244/569592 [5:19:24<457:38:59,  3.09s/it]
                                                            

  6%|▋         | 36244/569592 [5:19:24<457:38:59,  3.09s/it]
  6%|▋         | 36245/569592 [5:19:25<360:22:39,  2.43s/it]
                                                            

  6%|▋         | 36245/569592 [5:19:25<360:22:39,  2.43s/it]
  6%|▋         | 36246/569592 [5:19:26<299:01:22,  2.02s/it]
                                                            

  6%|▋         | 36246/569592 [5:19:26<299:01:22,  2.02s/it]
  6%|▋         | 36247/569592 [5:19:29<373:13:14,  2.52s/it]
                                                            

  6%|▋         | 36247/569592 [5:19:29<373:13:14,  2.52s/it]
  6%|▋         | 36248/569592 [5:19:34<485:17:13,  3.28s/it]
                                                            

  6%|▋         | 36248/569592 [5:19:34<485:17:13,  3.28s/it]
  6%|▋         | 36249/569592 [5:19:38<498:33:35,  3.37s/it]
                                                            

  6%|▋         | 36249/569592 [5:19:38<498:33:35,  3.37s/it]
  6%|▋         | 36250/569592 [5:19:41<495:35:50,  3.35s/it]
                                                            

  6%|▋         | 36250/569592 [5:19:41<495:35:50,  3.35s/it]
  6%|▋         | 36251/569592 [5:19:44<492:52:42,  3.33s/it]
                                                            

  6%|▋         | 36251/569592 [5:19:44<492:52:42,  3.33s/it]
  6%|▋         | 36252/569592 [5:19:50<599:41:21,  4.05s/it]
                                                            

  6%|▋         | 36252/569592 [5:19:50<599:41:21,  4.05s/it]
  6%|▋         | 36253/569592 [5:19:54<571:46:30,  3.86s/it]
                                                            

  6%|▋         | 36253/569592 [5:19:54<571:46:30,  3.86s/it]
  6%|▋         | 36254/569592 [5:19:57<542:08:09,  3.66s/it]
                                                            

  6%|▋         | 36254/569592 [5:19:57<542:08:09,  3.66s/it]
  6%|▋         | 36255/569592 [5:20:00<527:31:05,  3.56s/it]
                                                            

  6%|▋         | 36255/569592 [5:20:00<527:31:05,  3.56s/it]
  6%|▋         | 36256/569592 [5:20:04<521:43:43,  3.52s/it]
                                                            

  6%|▋         | 36256/569592 [5:20:04<521:43:43,  3.52s/it]
  6%|▋         | 36257/569592 [5:20:07<508:52:03,  3.43s/it]
                                                            

  6%|▋         | 36257/569592 [5:20:07<508:52:03,  3.43s/it]
  6%|▋         | 36258/569592 [5:20:08<402:36:19,  2.72s/it]
                                                            

  6%|▋         | 36258/569592 [5:20:08<402:36:19,  2.72s/it]
  6%|▋         | 36259/569592 [5:20:09<323:50:53,  2.19s/it]
                                                            

  6%|▋         | 36259/569592 [5:20:09<323:50:53,  2.19s/it]
  6%|▋         | 36260/569592 [5:20:12<384:33:35,  2.60s/it]
                                                            

  6%|▋         | 36260/569592 [5:20:12<384:33:35,  2.60s/it]
  6%|▋         | 36261/569592 [5:20:16<440:16:50,  2.97s/it]
                                                            

  6%|▋         | 36261/569592 [5:20:16<440:16:50,  2.97s/it]
  6%|▋         | 36262/569592 [5:20:21<518:11:48,  3.50s/it]
                                                            

  6%|▋         | 36262/569592 [5:20:21<518:11:48,  3.50s/it]
  6%|▋         | 36263/569592 [5:20:24<511:29:42,  3.45s/it]
                                                            

  6%|▋         | 36263/569592 [5:20:24<511:29:42,  3.45s/it]
  6%|▋         | 36264/569592 [5:20:28<508:03:47,  3.43s/it]
                                                            

  6%|▋         | 36264/569592 [5:20:28<508:03:47,  3.43s/it]
  6%|▋         | 36265/569592 [5:20:29<395:10:28,  2.67s/it]
                                                            

  6%|▋         | 36265/569592 [5:20:29<395:10:28,  2.67s/it]
  6%|▋         | 36266/569592 [5:20:32<428:56:48,  2.90s/it]
                                                            

  6%|▋         | 36266/569592 [5:20:32<428:56:48,  2.90s/it]
  6%|▋         | 36267/569592 [5:20:33<342:41:25,  2.31s/it]
                                                            

  6%|▋         | 36267/569592 [5:20:33<342:41:25,  2.31s/it]
  6%|▋         | 36268/569592 [5:20:37<411:57:47,  2.78s/it]
                                                            

  6%|▋         | 36268/569592 [5:20:37<411:57:47,  2.78s/it]
  6%|▋         | 36269/569592 [5:20:40<450:31:02,  3.04s/it]
                                                            

  6%|▋         | 36269/569592 [5:20:40<450:31:02,  3.04s/it]
  6%|▋         | 36270/569592 [5:20:41<357:47:42,  2.42s/it]
                                                            

  6%|▋         | 36270/569592 [5:20:41<357:47:42,  2.42s/it]
  6%|▋         | 36271/569592 [5:20:42<296:12:19,  2.00s/it]
                                                            

  6%|▋         | 36271/569592 [5:20:42<296:12:19,  2.00s/it]
  6%|▋         | 36272/569592 [5:20:46<360:46:24,  2.44s/it]
                                                            

  6%|▋         | 36272/569592 [5:20:46<360:46:24,  2.44s/it]
  6%|▋         | 36273/569592 [5:20:50<416:00:14,  2.81s/it]
                                                            

  6%|▋         | 36273/569592 [5:20:50<416:00:14,  2.81s/it]
  6%|▋         | 36274/569592 [5:20:53<441:04:48,  2.98s/it]
                                                            

  6%|▋         | 36274/569592 [5:20:53<441:04:48,  2.98s/it]
  6%|▋         | 36275/569592 [5:20:56<463:49:29,  3.13s/it]
                                                            

  6%|▋         | 36275/569592 [5:20:56<463:49:29,  3.13s/it]
  6%|▋         | 36276/569592 [5:20:57<364:36:13,  2.46s/it]
                                                            

  6%|▋         | 36276/569592 [5:20:57<364:36:13,  2.46s/it]
  6%|▋         | 36277/569592 [5:20:58<296:46:30,  2.00s/it]
                                                            

  6%|▋         | 36277/569592 [5:20:58<296:46:30,  2.00s/it]
  6%|▋         | 36278/569592 [5:21:02<359:30:21,  2.43s/it]
                                                            

  6%|▋         | 36278/569592 [5:21:02<359:30:21,  2.43s/it]
  6%|▋         | 36279/569592 [5:21:05<404:11:13,  2.73s/it]
                                                            

  6%|▋         | 36279/569592 [5:21:05<404:11:13,  2.73s/it]
  6%|▋         | 36280/569592 [5:21:06<326:17:11,  2.20s/it]
                                                            

  6%|▋         | 36280/569592 [5:21:06<326:17:11,  2.20s/it]
  6%|▋         | 36281/569592 [5:21:07<270:21:33,  1.83s/it]
                                                            

  6%|▋         | 36281/569592 [5:21:07<270:21:33,  1.83s/it]
  6%|▋         | 36282/569592 [5:21:08<230:57:14,  1.56s/it]
                                                            

  6%|▋         | 36282/569592 [5:21:08<230:57:14,  1.56s/it]
  6%|▋         | 36283/569592 [5:21:09<203:38:14,  1.37s/it]
                                                            

  6%|▋         | 36283/569592 [5:21:09<203:38:14,  1.37s/it]
  6%|▋         | 36284/569592 [5:21:12<303:18:05,  2.05s/it]
                                                            

  6%|▋         | 36284/569592 [5:21:12<303:18:05,  2.05s/it]
  6%|▋         | 36285/569592 [5:21:13<256:04:35,  1.73s/it]
                                                            

  6%|▋         | 36285/569592 [5:21:13<256:04:35,  1.73s/it]
  6%|▋         | 36286/569592 [5:21:14<222:02:35,  1.50s/it]
                                                            

  6%|▋         | 36286/569592 [5:21:14<222:02:35,  1.50s/it]
  6%|▋         | 36287/569592 [5:21:16<232:19:55,  1.57s/it]
                                                            

  6%|▋         | 36287/569592 [5:21:16<232:19:55,  1.57s/it]
  6%|▋         | 36288/569592 [5:21:23<463:59:21,  3.13s/it]
                                                            

  6%|▋         | 36288/569592 [5:21:23<463:59:21,  3.13s/it]
  6%|▋         | 36289/569592 [5:21:24<373:28:08,  2.52s/it]
                                                            

  6%|▋         | 36289/569592 [5:21:24<373:28:08,  2.52s/it]
  6%|▋         | 36290/569592 [5:21:27<403:22:14,  2.72s/it]
                                                            

  6%|▋         | 36290/569592 [5:21:27<403:22:14,  2.72s/it]
  6%|▋         | 36291/569592 [5:21:28<325:52:38,  2.20s/it]
                                                            

  6%|▋         | 36291/569592 [5:21:28<325:52:38,  2.20s/it]
  6%|▋         | 36292/569592 [5:21:31<340:52:54,  2.30s/it]
                                                            

  6%|▋         | 36292/569592 [5:21:31<340:52:54,  2.30s/it]
  6%|▋         | 36293/569592 [5:21:32<300:14:12,  2.03s/it]
                                                            

  6%|▋         | 36293/569592 [5:21:32<300:14:12,  2.03s/it]
  6%|▋         | 36294/569592 [5:21:39<499:33:03,  3.37s/it]
                                                            

  6%|▋         | 36294/569592 [5:21:39<499:33:03,  3.37s/it]
  6%|▋         | 36295/569592 [5:21:40<396:16:30,  2.68s/it]
                                                            

  6%|▋         | 36295/569592 [5:21:40<396:16:30,  2.68s/it]
  6%|▋         | 36296/569592 [5:21:43<433:59:54,  2.93s/it]
                                                            

  6%|▋         | 36296/569592 [5:21:43<433:59:54,  2.93s/it]
  6%|▋         | 36297/569592 [5:21:44<350:50:58,  2.37s/it]
                                                            

  6%|▋         | 36297/569592 [5:21:44<350:50:58,  2.37s/it]
  6%|▋         | 36298/569592 [5:21:48<394:30:22,  2.66s/it]
                                                            

  6%|▋         | 36298/569592 [5:21:48<394:30:22,  2.66s/it]
  6%|▋         | 36299/569592 [5:21:49<319:20:16,  2.16s/it]
                                                            

  6%|▋         | 36299/569592 [5:21:49<319:20:16,  2.16s/it]
  6%|▋         | 36300/569592 [5:21:52<357:38:26,  2.41s/it]
                                                            

  6%|▋         | 36300/569592 [5:21:52<357:38:26,  2.41s/it]
  6%|▋         | 36301/569592 [5:21:53<293:17:36,  1.98s/it]
                                                            

  6%|▋         | 36301/569592 [5:21:53<293:17:36,  1.98s/it]
  6%|▋         | 36302/569592 [5:21:57<383:06:55,  2.59s/it]
                                                            

  6%|▋         | 36302/569592 [5:21:57<383:06:55,  2.59s/it]
  6%|▋         | 36303/569592 [5:22:00<422:09:34,  2.85s/it]
                                                            

  6%|▋         | 36303/569592 [5:22:00<422:09:34,  2.85s/it]
  6%|▋         | 36304/569592 [5:22:01<343:10:23,  2.32s/it]
                                                            

  6%|▋         | 36304/569592 [5:22:01<343:10:23,  2.32s/it]
  6%|▋         | 36305/569592 [5:22:04<387:47:42,  2.62s/it]
                                                            

  6%|▋         | 36305/569592 [5:22:04<387:47:42,  2.62s/it]
  6%|▋         | 36306/569592 [5:22:07<371:16:02,  2.51s/it]
                                                            

  6%|▋         | 36306/569592 [5:22:07<371:16:02,  2.51s/it]
  6%|▋         | 36307/569592 [5:22:11<430:01:45,  2.90s/it]
                                                            

  6%|▋         | 36307/569592 [5:22:11<430:01:45,  2.90s/it]
  6%|▋         | 36308/569592 [5:22:14<475:17:41,  3.21s/it]
                                                            

  6%|▋         | 36308/569592 [5:22:14<475:17:41,  3.21s/it]
  6%|▋         | 36309/569592 [5:22:20<563:11:36,  3.80s/it]
                                                            

  6%|▋         | 36309/569592 [5:22:20<563:11:36,  3.80s/it]
  6%|▋         | 36310/569592 [5:22:23<544:46:33,  3.68s/it]
                                                            

  6%|▋         | 36310/569592 [5:22:23<544:46:33,  3.68s/it]
  6%|▋         | 36311/569592 [5:22:24<424:36:45,  2.87s/it]
                                                            

  6%|▋         | 36311/569592 [5:22:24<424:36:45,  2.87s/it]
  6%|▋         | 36312/569592 [5:22:25<338:56:29,  2.29s/it]
                                                            

  6%|▋         | 36312/569592 [5:22:25<338:56:29,  2.29s/it]
  6%|▋         | 36313/569592 [5:22:29<400:22:09,  2.70s/it]
                                                            

  6%|▋         | 36313/569592 [5:22:29<400:22:09,  2.70s/it]
  6%|▋         | 36314/569592 [5:22:32<441:50:12,  2.98s/it]
                                                            

  6%|▋         | 36314/569592 [5:22:32<441:50:12,  2.98s/it]
  6%|▋         | 36315/569592 [5:22:33<351:28:26,  2.37s/it]
                                                            

  6%|▋         | 36315/569592 [5:22:33<351:28:26,  2.37s/it]
  6%|▋         | 36316/569592 [5:22:34<288:47:40,  1.95s/it]
                                                            

  6%|▋         | 36316/569592 [5:22:34<288:47:40,  1.95s/it]
  6%|▋         | 36317/569592 [5:22:35<245:59:50,  1.66s/it]
                                                            

  6%|▋         | 36317/569592 [5:22:35<245:59:50,  1.66s/it]
  6%|▋         | 36318/569592 [5:22:39<335:22:17,  2.26s/it]
                                                            

  6%|▋         | 36318/569592 [5:22:39<335:22:17,  2.26s/it]
  6%|▋         | 36319/569592 [5:22:42<395:32:33,  2.67s/it]
                                                            

  6%|▋         | 36319/569592 [5:22:42<395:32:33,  2.67s/it]
  6%|▋         | 36320/569592 [5:22:46<437:52:14,  2.96s/it]
                                                            

  6%|▋         | 36320/569592 [5:22:46<437:52:14,  2.96s/it]
  6%|▋         | 36321/569592 [5:22:50<469:24:37,  3.17s/it]
                                                            

  6%|▋         | 36321/569592 [5:22:50<469:24:37,  3.17s/it]
  6%|▋         | 36322/569592 [5:22:53<472:32:28,  3.19s/it]
                                                            

  6%|▋         | 36322/569592 [5:22:53<472:32:28,  3.19s/it]
  6%|▋         | 36323/569592 [5:22:54<373:36:07,  2.52s/it]
                                                            

  6%|▋         | 36323/569592 [5:22:54<373:36:07,  2.52s/it]
  6%|▋         | 36324/569592 [5:22:57<413:07:40,  2.79s/it]
                                                            

  6%|▋         | 36324/569592 [5:22:57<413:07:40,  2.79s/it]
  6%|▋         | 36325/569592 [5:23:01<438:43:53,  2.96s/it]
                                                            

  6%|▋         | 36325/569592 [5:23:01<438:43:53,  2.96s/it]
  6%|▋         | 36326/569592 [5:23:02<348:20:42,  2.35s/it]
                                                            

  6%|▋         | 36326/569592 [5:23:02<348:20:42,  2.35s/it]
  6%|▋         | 36327/569592 [5:23:07<469:51:18,  3.17s/it]
                                                            

  6%|▋         | 36327/569592 [5:23:07<469:51:18,  3.17s/it]
  6%|▋         | 36328/569592 [5:23:08<369:15:06,  2.49s/it]
                                                            

  6%|▋         | 36328/569592 [5:23:08<369:15:06,  2.49s/it]
  6%|▋         | 36329/569592 [5:23:11<398:34:07,  2.69s/it]
                                                            

  6%|▋         | 36329/569592 [5:23:11<398:34:07,  2.69s/it]
  6%|▋         | 36330/569592 [5:23:12<320:38:08,  2.16s/it]
                                                            

  6%|▋         | 36330/569592 [5:23:12<320:38:08,  2.16s/it]
  6%|▋         | 36331/569592 [5:23:13<268:58:01,  1.82s/it]
                                                            

  6%|▋         | 36331/569592 [5:23:13<268:58:01,  1.82s/it]
  6%|▋         | 36332/569592 [5:23:16<344:11:25,  2.32s/it]
                                                            

  6%|▋         | 36332/569592 [5:23:16<344:11:25,  2.32s/it]
  6%|▋         | 36333/569592 [5:23:20<414:08:52,  2.80s/it]
                                                            

  6%|▋         | 36333/569592 [5:23:20<414:08:52,  2.80s/it]
  6%|▋         | 36334/569592 [5:23:25<507:22:12,  3.43s/it]
                                                            

  6%|▋         | 36334/569592 [5:23:25<507:22:12,  3.43s/it]
  6%|▋         | 36335/569592 [5:23:28<490:43:56,  3.31s/it]
                                                            

  6%|▋         | 36335/569592 [5:23:28<490:43:56,  3.31s/it]
  6%|▋         | 36336/569592 [5:23:33<550:45:09,  3.72s/it]
                                                            

  6%|▋         | 36336/569592 [5:23:33<550:45:09,  3.72s/it]
  6%|▋         | 36337/569592 [5:23:34<425:27:41,  2.87s/it]
                                                            

  6%|▋         | 36337/569592 [5:23:34<425:27:41,  2.87s/it]
  6%|▋         | 36338/569592 [5:23:37<451:10:28,  3.05s/it]
                                                            

  6%|▋         | 36338/569592 [5:23:37<451:10:28,  3.05s/it]
  6%|▋         | 36339/569592 [5:23:38<357:29:22,  2.41s/it]
                                                            

  6%|▋         | 36339/569592 [5:23:38<357:29:22,  2.41s/it]
  6%|▋         | 36340/569592 [5:23:39<293:45:34,  1.98s/it]
                                                            

  6%|▋         | 36340/569592 [5:23:39<293:45:34,  1.98s/it]
  6%|▋         | 36341/569592 [5:23:43<363:31:04,  2.45s/it]
                                                            

  6%|▋         | 36341/569592 [5:23:43<363:31:04,  2.45s/it]
  6%|▋         | 36342/569592 [5:23:46<414:33:39,  2.80s/it]
                                                            

  6%|▋         | 36342/569592 [5:23:46<414:33:39,  2.80s/it]
  6%|▋         | 36343/569592 [5:23:50<446:45:05,  3.02s/it]
                                                            

  6%|▋         | 36343/569592 [5:23:50<446:45:05,  3.02s/it]
  6%|▋         | 36344/569592 [5:23:53<474:27:35,  3.20s/it]
                                                            

  6%|▋         | 36344/569592 [5:23:53<474:27:35,  3.20s/it]
  6%|▋         | 36345/569592 [5:23:58<531:05:43,  3.59s/it]
                                                            

  6%|▋         | 36345/569592 [5:23:58<531:05:43,  3.59s/it]
  6%|▋         | 36346/569592 [5:24:01<531:35:18,  3.59s/it]
                                                            

  6%|▋         | 36346/569592 [5:24:01<531:35:18,  3.59s/it]
  6%|▋         | 36347/569592 [5:24:05<533:35:36,  3.60s/it]
                                                            

  6%|▋         | 36347/569592 [5:24:05<533:35:36,  3.60s/it]
  6%|▋         | 36348/569592 [5:24:08<504:29:33,  3.41s/it]
                                                            

  6%|▋         | 36348/569592 [5:24:08<504:29:33,  3.41s/it]
  6%|▋         | 36349/569592 [5:24:09<393:12:34,  2.65s/it]
                                                            

  6%|▋         | 36349/569592 [5:24:09<393:12:34,  2.65s/it]
  6%|▋         | 36350/569592 [5:24:12<428:12:50,  2.89s/it]
                                                            

  6%|▋         | 36350/569592 [5:24:12<428:12:50,  2.89s/it]
  6%|▋         | 36351/569592 [5:24:16<483:12:54,  3.26s/it]
                                                            

  6%|▋         | 36351/569592 [5:24:16<483:12:54,  3.26s/it]
  6%|▋         | 36352/569592 [5:24:20<497:47:38,  3.36s/it]
                                                            

  6%|▋         | 36352/569592 [5:24:20<497:47:38,  3.36s/it]
  6%|▋         | 36353/569592 [5:24:24<510:53:23,  3.45s/it]
                                                            

  6%|▋         | 36353/569592 [5:24:24<510:53:23,  3.45s/it]
  6%|▋         | 36354/569592 [5:24:28<566:13:25,  3.82s/it]
                                                            

  6%|▋         | 36354/569592 [5:24:28<566:13:25,  3.82s/it]
  6%|▋         | 36355/569592 [5:24:29<435:05:24,  2.94s/it]
                                                            

  6%|▋         | 36355/569592 [5:24:29<435:05:24,  2.94s/it]
  6%|▋         | 36356/569592 [5:24:34<533:15:02,  3.60s/it]
                                                            

  6%|▋         | 36356/569592 [5:24:34<533:15:02,  3.60s/it]
  6%|▋         | 36357/569592 [5:24:38<511:41:08,  3.45s/it]
                                                            

  6%|▋         | 36357/569592 [5:24:38<511:41:08,  3.45s/it]
  6%|▋         | 36358/569592 [5:24:41<502:47:02,  3.39s/it]
                                                            

  6%|▋         | 36358/569592 [5:24:41<502:47:02,  3.39s/it]
  6%|▋         | 36359/569592 [5:24:44<501:52:32,  3.39s/it]
                                                            

  6%|▋         | 36359/569592 [5:24:44<501:52:32,  3.39s/it]
  6%|▋         | 36360/569592 [5:24:48<503:58:41,  3.40s/it]
                                                            

  6%|▋         | 36360/569592 [5:24:48<503:58:41,  3.40s/it]
  6%|▋         | 36361/569592 [5:24:51<503:46:01,  3.40s/it]
                                                            

  6%|▋         | 36361/569592 [5:24:51<503:46:01,  3.40s/it]
  6%|▋         | 36362/569592 [5:24:52<392:33:18,  2.65s/it]
                                                            

  6%|▋         | 36362/569592 [5:24:52<392:33:18,  2.65s/it]
  6%|▋         | 36363/569592 [5:24:55<432:35:57,  2.92s/it]
                                                            

  6%|▋         | 36363/569592 [5:24:55<432:35:57,  2.92s/it]
  6%|▋         | 36364/569592 [5:24:59<464:30:16,  3.14s/it]
                                                            

  6%|▋         | 36364/569592 [5:24:59<464:30:16,  3.14s/it]
  6%|▋         | 36365/569592 [5:25:02<472:33:31,  3.19s/it]
                                                            

  6%|▋         | 36365/569592 [5:25:02<472:33:31,  3.19s/it]
  6%|▋         | 36366/569592 [5:25:07<534:03:59,  3.61s/it]
                                                            

  6%|▋         | 36366/569592 [5:25:07<534:03:59,  3.61s/it]
  6%|▋         | 36367/569592 [5:25:10<528:15:14,  3.57s/it]
                                                            

  6%|▋         | 36367/569592 [5:25:10<528:15:14,  3.57s/it]
  6%|▋         | 36368/569592 [5:25:14<517:44:29,  3.50s/it]
                                                            

  6%|▋         | 36368/569592 [5:25:14<517:44:29,  3.50s/it]
  6%|▋         | 36369/569592 [5:25:18<565:14:27,  3.82s/it]
                                                            

  6%|▋         | 36369/569592 [5:25:18<565:14:27,  3.82s/it]
  6%|▋         | 36370/569592 [5:25:22<545:02:01,  3.68s/it]
                                                            

  6%|▋         | 36370/569592 [5:25:22<545:02:01,  3.68s/it]
  6%|▋         | 36371/569592 [5:25:25<518:25:18,  3.50s/it]
                                                            

  6%|▋         | 36371/569592 [5:25:25<518:25:18,  3.50s/it]
  6%|▋         | 36372/569592 [5:25:26<403:40:26,  2.73s/it]
                                                            

  6%|▋         | 36372/569592 [5:25:26<403:40:26,  2.73s/it]
  6%|▋         | 36373/569592 [5:25:27<324:36:18,  2.19s/it]
                                                            

  6%|▋         | 36373/569592 [5:25:27<324:36:18,  2.19s/it]
  6%|▋         | 36374/569592 [5:25:31<406:08:05,  2.74s/it]
                                                            

  6%|▋         | 36374/569592 [5:25:31<406:08:05,  2.74s/it]
  6%|▋         | 36375/569592 [5:25:32<329:59:16,  2.23s/it]
                                                            

  6%|▋         | 36375/569592 [5:25:32<329:59:16,  2.23s/it]
  6%|▋         | 36376/569592 [5:25:33<278:06:38,  1.88s/it]
                                                            

  6%|▋         | 36376/569592 [5:25:33<278:06:38,  1.88s/it]
  6%|▋         | 36377/569592 [5:25:34<237:12:01,  1.60s/it]
                                                            

  6%|▋         | 36377/569592 [5:25:34<237:12:01,  1.60s/it]
  6%|▋         | 36378/569592 [5:25:37<315:24:51,  2.13s/it]
                                                            

  6%|▋         | 36378/569592 [5:25:37<315:24:51,  2.13s/it]
  6%|▋         | 36379/569592 [5:25:41<405:30:29,  2.74s/it]
                                                            

  6%|▋         | 36379/569592 [5:25:41<405:30:29,  2.74s/it]
  6%|▋         | 36380/569592 [5:25:45<430:12:33,  2.90s/it]
                                                            

  6%|▋         | 36380/569592 [5:25:45<430:12:33,  2.90s/it]
  6%|▋         | 36381/569592 [5:25:48<469:42:54,  3.17s/it]
                                                            

  6%|▋         | 36381/569592 [5:25:48<469:42:54,  3.17s/it]
  6%|▋         | 36382/569592 [5:25:51<469:48:42,  3.17s/it]
                                                            

  6%|▋         | 36382/569592 [5:25:51<469:48:42,  3.17s/it]
  6%|▋         | 36383/569592 [5:25:52<371:07:05,  2.51s/it]
                                                            

  6%|▋         | 36383/569592 [5:25:52<371:07:05,  2.51s/it]
  6%|▋         | 36384/569592 [5:25:56<403:17:53,  2.72s/it]
                                                            

  6%|▋         | 36384/569592 [5:25:56<403:17:53,  2.72s/it]
  6%|▋         | 36385/569592 [5:25:57<323:54:52,  2.19s/it]
                                                            

  6%|▋         | 36385/569592 [5:25:57<323:54:52,  2.19s/it]
  6%|▋         | 36386/569592 [5:26:01<411:01:21,  2.78s/it]
                                                            

  6%|▋         | 36386/569592 [5:26:01<411:01:21,  2.78s/it]
  6%|▋         | 36387/569592 [5:26:04<430:46:35,  2.91s/it]
                                                            

  6%|▋         | 36387/569592 [5:26:04<430:46:35,  2.91s/it]
  6%|▋         | 36388/569592 [5:26:07<451:45:20,  3.05s/it]
                                                            

  6%|▋         | 36388/569592 [5:26:07<451:45:20,  3.05s/it]
  6%|▋         | 36389/569592 [5:26:08<357:40:03,  2.41s/it]
                                                            

  6%|▋         | 36389/569592 [5:26:08<357:40:03,  2.41s/it]
  6%|▋         | 36390/569592 [5:26:09<292:32:37,  1.98s/it]
                                                            

  6%|▋         | 36390/569592 [5:26:09<292:32:37,  1.98s/it]
  6%|▋         | 36391/569592 [5:26:14<421:44:30,  2.85s/it]
                                                            

  6%|▋         | 36391/569592 [5:26:14<421:44:30,  2.85s/it]
  6%|▋         | 36392/569592 [5:26:15<339:16:10,  2.29s/it]
                                                            

  6%|▋         | 36392/569592 [5:26:15<339:16:10,  2.29s/it]
  6%|▋         | 36393/569592 [5:26:16<278:24:56,  1.88s/it]
                                                            

  6%|▋         | 36393/569592 [5:26:16<278:24:56,  1.88s/it]
  6%|▋         | 36394/569592 [5:26:17<235:32:41,  1.59s/it]
                                                            

  6%|▋         | 36394/569592 [5:26:17<235:32:41,  1.59s/it]
  6%|▋         | 36395/569592 [5:26:18<206:07:01,  1.39s/it]
                                                            

  6%|▋         | 36395/569592 [5:26:18<206:07:01,  1.39s/it]
  6%|▋         | 36396/569592 [5:26:19<194:32:36,  1.31s/it]
                                                            

  6%|▋         | 36396/569592 [5:26:19<194:32:36,  1.31s/it]
  6%|▋         | 36397/569592 [5:26:22<290:01:42,  1.96s/it]
                                                            

  6%|▋         | 36397/569592 [5:26:22<290:01:42,  1.96s/it]
  6%|▋         | 36398/569592 [5:26:23<245:59:34,  1.66s/it]
                                                            

  6%|▋         | 36398/569592 [5:26:23<245:59:34,  1.66s/it]
  6%|▋         | 36399/569592 [5:26:27<350:31:38,  2.37s/it]
                                                            

  6%|▋         | 36399/569592 [5:26:27<350:31:38,  2.37s/it]
  6%|▋         | 36400/569592 [5:26:29<325:54:08,  2.20s/it]
                                                            

  6%|▋         | 36400/569592 [5:26:29<325:54:08,  2.20s/it]
  6%|▋         | 36401/569592 [5:26:32<339:36:31,  2.29s/it]
                                                            

  6%|▋         | 36401/569592 [5:26:32<339:36:31,  2.29s/it]
  6%|▋         | 36402/569592 [5:26:33<282:26:02,  1.91s/it]
                                                            

  6%|▋         | 36402/569592 [5:26:33<282:26:02,  1.91s/it]
  6%|▋         | 36403/569592 [5:26:38<416:16:28,  2.81s/it]
                                                            

  6%|▋         | 36403/569592 [5:26:38<416:16:28,  2.81s/it]
  6%|▋         | 36404/569592 [5:26:40<416:37:44,  2.81s/it]
                                                            

  6%|▋         | 36404/569592 [5:26:41<416:37:44,  2.81s/it]
  6%|▋         | 36405/569592 [5:26:44<452:41:59,  3.06s/it]
                                                            

  6%|▋         | 36405/569592 [5:26:44<452:41:59,  3.06s/it]
  6%|▋         | 36406/569592 [5:26:45<360:00:14,  2.43s/it]
                                                            

  6%|▋         | 36406/569592 [5:26:45<360:00:14,  2.43s/it]
  6%|▋         | 36407/569592 [5:26:49<405:24:13,  2.74s/it]
                                                            

  6%|▋         | 36407/569592 [5:26:49<405:24:13,  2.74s/it]
  6%|▋         | 36408/569592 [5:26:51<390:46:56,  2.64s/it]
                                                            

  6%|▋         | 36408/569592 [5:26:51<390:46:56,  2.64s/it]
  6%|▋         | 36409/569592 [5:26:56<496:59:50,  3.36s/it]
                                                            

  6%|▋         | 36409/569592 [5:26:56<496:59:50,  3.36s/it]
  6%|▋         | 36410/569592 [5:26:57<390:24:32,  2.64s/it]
                                                            

  6%|▋         | 36410/569592 [5:26:57<390:24:32,  2.64s/it]
  6%|▋         | 36411/569592 [5:26:58<314:10:42,  2.12s/it]
                                                            

  6%|▋         | 36411/569592 [5:26:58<314:10:42,  2.12s/it]
  6%|▋         | 36412/569592 [5:27:01<346:57:29,  2.34s/it]
                                                            

  6%|▋         | 36412/569592 [5:27:01<346:57:29,  2.34s/it]
  6%|▋         | 36413/569592 [5:27:04<392:48:07,  2.65s/it]
                                                            

  6%|▋         | 36413/569592 [5:27:04<392:48:07,  2.65s/it]
  6%|▋         | 36414/569592 [5:27:05<316:27:28,  2.14s/it]
                                                            

  6%|▋         | 36414/569592 [5:27:05<316:27:28,  2.14s/it]
  6%|▋         | 36415/569592 [5:27:08<365:35:25,  2.47s/it]
                                                            

  6%|▋         | 36415/569592 [5:27:08<365:35:25,  2.47s/it]
  6%|▋         | 36416/569592 [5:27:11<370:04:33,  2.50s/it]
                                                            

  6%|▋         | 36416/569592 [5:27:11<370:04:33,  2.50s/it]
  6%|▋         | 36417/569592 [5:27:15<423:48:07,  2.86s/it]
                                                            

  6%|▋         | 36417/569592 [5:27:15<423:48:07,  2.86s/it]
  6%|▋         | 36418/569592 [5:27:16<339:51:01,  2.29s/it]
                                                            

  6%|▋         | 36418/569592 [5:27:16<339:51:01,  2.29s/it]
  6%|▋         | 36419/569592 [5:27:18<367:44:40,  2.48s/it]
                                                            

  6%|▋         | 36419/569592 [5:27:18<367:44:40,  2.48s/it]
  6%|▋         | 36420/569592 [5:27:22<412:02:18,  2.78s/it]
                                                            

  6%|▋         | 36420/569592 [5:27:22<412:02:18,  2.78s/it]
  6%|▋         | 36421/569592 [5:27:26<459:31:26,  3.10s/it]
                                                            

  6%|▋         | 36421/569592 [5:27:26<459:31:26,  3.10s/it]
  6%|▋         | 36422/569592 [5:27:27<364:37:12,  2.46s/it]
                                                            

  6%|▋         | 36422/569592 [5:27:27<364:37:12,  2.46s/it]
  6%|▋         | 36423/569592 [5:27:28<298:50:47,  2.02s/it]
                                                            

  6%|▋         | 36423/569592 [5:27:28<298:50:47,  2.02s/it]
  6%|▋         | 36424/569592 [5:27:32<402:07:26,  2.72s/it]
                                                            

  6%|▋         | 36424/569592 [5:27:32<402:07:26,  2.72s/it]
  6%|▋         | 36425/569592 [5:27:35<429:00:41,  2.90s/it]
                                                            

  6%|▋         | 36425/569592 [5:27:35<429:00:41,  2.90s/it]
  6%|▋         | 36426/569592 [5:27:39<465:31:27,  3.14s/it]
                                                            

  6%|▋         | 36426/569592 [5:27:39<465:31:27,  3.14s/it]
  6%|▋         | 36427/569592 [5:27:44<532:09:24,  3.59s/it]
                                                            

  6%|▋         | 36427/569592 [5:27:44<532:09:24,  3.59s/it]
  6%|▋         | 36428/569592 [5:27:45<422:32:05,  2.85s/it]
                                                            

  6%|▋         | 36428/569592 [5:27:45<422:32:05,  2.85s/it]
  6%|▋         | 36429/569592 [5:27:46<336:25:08,  2.27s/it]
                                                            

  6%|▋         | 36429/569592 [5:27:46<336:25:08,  2.27s/it]
  6%|▋         | 36430/569592 [5:27:47<276:38:48,  1.87s/it]
                                                            

  6%|▋         | 36430/569592 [5:27:47<276:38:48,  1.87s/it]
  6%|▋         | 36431/569592 [5:27:50<341:51:34,  2.31s/it]
                                                            

  6%|▋         | 36431/569592 [5:27:50<341:51:34,  2.31s/it]
  6%|▋         | 36432/569592 [5:27:52<317:14:22,  2.14s/it]
                                                            

  6%|▋         | 36432/569592 [5:27:52<317:14:22,  2.14s/it]
  6%|▋         | 36433/569592 [5:27:57<449:11:30,  3.03s/it]
                                                            

  6%|▋         | 36433/569592 [5:27:57<449:11:30,  3.03s/it]
  6%|▋         | 36434/569592 [5:27:58<359:09:54,  2.43s/it]
                                                            

  6%|▋         | 36434/569592 [5:27:58<359:09:54,  2.43s/it]
  6%|▋         | 36435/569592 [5:28:01<407:16:42,  2.75s/it]
                                                            

  6%|▋         | 36435/569592 [5:28:01<407:16:42,  2.75s/it]
  6%|▋         | 36436/569592 [5:28:05<441:57:59,  2.98s/it]
                                                            

  6%|▋         | 36436/569592 [5:28:05<441:57:59,  2.98s/it]
  6%|▋         | 36437/569592 [5:28:10<523:30:51,  3.53s/it]
                                                            

  6%|▋         | 36437/569592 [5:28:10<523:30:51,  3.53s/it]
  6%|▋         | 36438/569592 [5:28:14<575:54:54,  3.89s/it]
                                                            

  6%|▋         | 36438/569592 [5:28:15<575:54:54,  3.89s/it]
  6%|▋         | 36439/569592 [5:28:18<542:55:06,  3.67s/it]
                                                            

  6%|▋         | 36439/569592 [5:28:18<542:55:06,  3.67s/it]
  6%|▋         | 36440/569592 [5:28:21<542:01:42,  3.66s/it]
                                                            

  6%|▋         | 36440/569592 [5:28:21<542:01:42,  3.66s/it]
  6%|▋         | 36441/569592 [5:28:22<421:22:28,  2.85s/it]
                                                            

  6%|▋         | 36441/569592 [5:28:22<421:22:28,  2.85s/it]
  6%|▋         | 36442/569592 [5:28:23<340:15:29,  2.30s/it]
                                                            

  6%|▋         | 36442/569592 [5:28:23<340:15:29,  2.30s/it]
  6%|▋         | 36443/569592 [5:28:24<281:36:45,  1.90s/it]
                                                            

  6%|▋         | 36443/569592 [5:28:24<281:36:45,  1.90s/it]
  6%|▋         | 36444/569592 [5:28:28<346:10:06,  2.34s/it]
                                                            

  6%|▋         | 36444/569592 [5:28:28<346:10:06,  2.34s/it]
  6%|▋         | 36445/569592 [5:28:31<388:04:19,  2.62s/it]
                                                            

  6%|▋         | 36445/569592 [5:28:31<388:04:19,  2.62s/it]
  6%|▋         | 36446/569592 [5:28:35<459:01:58,  3.10s/it]
                                                            

  6%|▋         | 36446/569592 [5:28:35<459:01:58,  3.10s/it]
  6%|▋         | 36447/569592 [5:28:38<466:59:32,  3.15s/it]
                                                            

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  6%|▋         | 36529/569592 [5:32:/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90316800 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
28<495:26:12,  3.35s/it]
                                                            

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  warnings.warn(

                                                            

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  6%|▋         | 36/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  warnings.warn(
53:24:38,  3.06s/it]
                                                            

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                       /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (92621766 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                     

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  warnings.warn(
1,  3.17s/it]
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                                   /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                         

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  6%|▋         | 36753/569592 [5:43:00<385:55:57,  2.61s/it]
  6%|▋         | 36754/569592 [5:43:02<342:06:43,  2.31s/it]
                                                            

  6%|▋         | 36754/569592 [5:43:02<342:06:43,  2.31s/it]
  6%|▋         | 36755/569592 [5:43:03<281:04:35,  1.90s/it]
                                                            

  6%|▋         | 36755/569592 [5:43:03<281:04:35,  1.90s/it]
  6%|▋         | 36756/569592 [5:43:09<469:39:59,  3.17s/it]
                                                            

  6%|▋         | 36756/569592 [5:43:09<469:39:59,  3.17s/it]
  6%|▋         | 36757/569592 [5:43:12<481:23:19,  3.25s/it]
                                                            

  6%|▋         | 36757/569592 [5:43:12<481:23:19,  3.25s/it]
  6%|▋         | 36758/569592 [5:43:16<513:35:48,  3.47s/it]
                                                            

  6%|▋         | 36758/569592 [5:43:16<513:35:48,  3.47s/it]
  6%|▋         | 36759/569592 [5:43:17<401:25:08,  2.71s/it]
                                                            

  6%|▋         | 36759/569592 [5:43:17<401:25:08,  2.71s/it]
  6%|▋         | 36760/569592 [5:43:21<438:41:57,  2.96s/it]
                                                            

  6%|▋         | 36760/569592 [5:43:21<438:41:57,  2.96s/it]
  6%|▋         | 36761/569592 [5:43:22<349:55:51,  2.36s/it]
                                                            

  6%|▋         | 36761/569592 [5:43:22<349:55:51,  2.36s/it]
  6%|▋         | 36762/569592 [5:43:23<289:45:28,  1.96s/it]
                                                            

  6%|▋         | 36762/569592 [5:43:23<289:45:28,  1.96s/it]
  6%|▋         | 36763/569592 [5:43:24<255:42:40,  1.73s/it]
                                                            

  6%|▋         | 36763/569592 [5:43:24<255:42:40,  1.73s/it]
  6%|▋         | 36764/569592 [5:43:32<527:00:35,  3.56s/it]
                                                            

  6%|▋         | 36764/569592 [5:43:32<527:00:35,  3.56s/it]
  6%|▋         | 36765/569592 [5:43:35<528:55:17,  3.57s/it]
                                                            

  6%|▋         | 36765/569592 [5:43:35<528:55:17,  3.57s/it]
  6%|▋         | 36766/569592 [5:43:36<411:04:48,  2.78s/it]
                                                            

  6%|▋         | 36766/569592 [5:43:36<411:04:48,  2.78s/it]
  6%|▋         | 36767/569592 [5:43:37<330:36:52,  2.23s/it]
                                                            

  6%|▋         | 36767/569592 [5:43:37<330:36:52,  2.23s/it]
  6%|▋         | 36768/569592 [5:43:40<365:47:29,  2.47s/it]
                                                            

  6%|▋         | 36768/569592 [5:43:40<365:47:29,  2.47s/it]
  6%|▋         | 36769/569592 [5:43:44<399:25:39,  2.70s/it]
                                                            

  6%|▋         | 36769/569592 [5:43:44<399:25:39,  2.70s/it]
  6%|▋         | 36770/569592 [5:43:45<322:39:00,  2.18s/it]
                                                            

  6%|▋         | 36770/569592 [5:43:45<322:39:00,  2.18s/it]
  6%|▋         | 36771/569592 [5:43:48<380:06:24,  2.57s/it]
                                                            

  6%|▋         | 36771/569592 [5:43:48<380:06:24,  2.57s/it]
  6%|▋         | 36772/569592 [5:43:50<354:46:49,  2.40s/it]
                                                            

  6%|▋         | 36772/569592 [5:43:50<354:46:49,  2.40s/it]
  6%|▋         | 36773/569592 [5:43:51<290:24:06,  1.96s/it]
                                                            

  6%|▋         | 36773/569592 [5:43:51<290:24:06,  1.96s/it]
  6%|▋         | 36774/569592 [5:43:54<353:47:27,  2.39s/it]
                                                            

  6%|▋         | 36774/569592 [5:43:54<353:47:27,  2.39s/it]
  6%|▋         | 36775/569592 [5:43:58<405:27:31,  2.74s/it]
                                                            

  6%|▋         | 36775/569592 [5:43:58<405:27:31,  2.74s/it]
  6%|▋         | 36776/569592 [5:44:02<453:34:45,  3.06s/it]
                                                            

  6%|▋         | 36776/569592 [5:44:02<453:34:45,  3.06s/it]
  6%|▋         | 36777/569592 [5:44:06<495:49:18,  3.35s/it]
                                                            

  6%|▋         | 36777/569592 [5:44:06<495:49:18,  3.35s/it]
  6%|▋         | 36778/569592 [5:44:07<392:49:05,  2.65s/it]
                                                            

  6%|▋         | 36778/569592 [5:44:07<392:49:05,  2.65s/it]
  6%|▋         | 36779/569592 [5:44:10<431:20:46,  2.91s/it]
                                                            

  6%|▋         | 36779/569592 [5:44:10<431:20:46,  2.91s/it]
  6%|▋         | 36780/569592 [5:44:16<532:46:27,  3.60s/it]
                                                            

  6%|▋         | 36780/569592 [5:44:16<532:46:27,  3.60s/it]
  6%|▋         | 36781/569592 [5:44:16<415:19:50,  2.81s/it]
                                                            

  6%|▋         | 36781/569592 [5:44:17<415:19:50,  2.81s/it]
  6%|▋         | 36782/569592 [5:44:20<426:10:57,  2.88s/it]
                                                            

  6%|▋         | 36782/569592 [5:44:20<426:10:57,  2.88s/it]
  6%|▋         | 36783/569592 [5:44:23<446:38:28,  3.02s/it]
                                                            

  6%|▋         | 36783/569592 [5:44:23<446:38:28,  3.02s/it]
  6%|▋         | 36784/569592 [5:44:26<462:58:56,  3.13s/it]
                                                            

  6%|▋         | 36784/569592 [5:44:26<462:58:56,  3.13s/it]
  6%|▋         | 36785/569592 [5:44:30<470:24:49,  3.18s/it]
                                                            

  6%|▋         | 36785/569592 [5:44:30<470:24:49,  3.18s/it]
  6%|▋         | 36786/569592 [5:44:34<507:03:43,  3.43s/it]
                                                            

  6%|▋         | 36786/569592 [5:44:34<507:03:43,  3.43s/it]
  6%|▋         | 36787/569592 [5:44:34<394:44:05,  2.67s/it]
                                                            

  6%|▋         | 36787/569592 [5:44:34<394:44:05,  2.67s/it]
  6%|▋         | 36788/569592 [5:44:38<433:39:34,  2.93s/it]
                                                            

  6%|▋         | 36788/569592 [5:44:38<433:39:34,  2.93s/it]
  6%|▋         | 36789/569592 [5:44:42<464:39:57,  3.14s/it]
                                                            

  6%|▋         | 36789/569592 [5:44:42<464:39:57,  3.14s/it]
  6%|▋         | 36790/569592 [5:44:46<533:04:40,  3.60s/it]
                                                            

  6%|▋         | 36790/569592 [5:44:46<533:04:40,  3.60s/it]
  6%|▋         | 36791/569592 [5:44:49<509:03:29,  3.44s/it]
                                                            

  6%|▋         | 36791/569592 [5:44:49<509:03:29,  3.44s/it]
  6%|▋         | 36792/569592 [5:44:53<507:08:16,  3.43s/it]
                                                            

  6%|▋         | 36792/569592 [5:44:53<507:08:16,  3.43s/it]
  6%|▋         | 36793/569592 [5:44:54<395:59:44,  2.68s/it]
                                                            

  6%|▋         | 36793/569592 [5:44:54<395:59:44,  2.68s/it]
  6%|▋         | 36794/569592 [5:44:57<435:47:44,  2.94s/it]
                                                            

  6%|▋         | 36794/569592 [5:44:57<435:47:44,  2.94s/it]
  6%|▋         | 36795/569592 [5:45:01<456:34:11,  3.08s/it]
                                                            

  6%|▋         | 36795/569592 [5:45:01<456:34:11,  3.08s/it]
  6%|▋         | 36796/569592 [5:45:04<473:30:00,  3.20s/it]
                                                            

  6%|▋         | 36796/569592 [5:45:04<473:30:00,  3.20s/it]
  6%|▋         | 36797/569592 [5:45:05<371:07:35,  2.51s/it]
                                                            

  6%|▋         | 36797/569592 [5:45:05<371:07:35,  2.51s/it]
  6%|▋         | 36798/569592 [5:45:09<414:07:07,  2.80s/it]
                                                            

  6%|▋         | 36798/569592 [5:45:09<414:07:07,  2.80s/it]
  6%|▋         | 36799/569592 [5:45:10<334:59:29,  2.26s/it]
                                                            

  6%|▋         | 36799/569592 [5:45:10<334:59:29,  2.26s/it]
  6%|▋         | 36800/569592 [5:45:13<393:11:55,  2.66s/it]
                                                            

  6%|▋         | 36800/569592 [5:45:13<393:11:55,  2.66s/it]
  6%|▋         | 36801/569592 [5:45:16<416:07:27,  2.81s/it]
                                                            

  6%|▋         | 36801/569592 [5:45:16<416:07:27,  2.81s/it]
  6%|▋         | 36802/569592 [5:45:20<444:42:10,  3.00s/it]
                                                            

  6%|▋         | 36802/569592 [5:45:20<444:42:10,  3.00s/it]
  6%|▋         | 36803/569592 [5:45:24<502:00:12,  3.39s/it]
                                                            

  6%|▋         | 36803/569592 [5:45:24<502:00:12,  3.39s/it]
  6%|▋         | 36804/569592 [5:45:27<502:32:41,  3.40s/it]
                                                            

  6%|▋         | 36804/569592 [5:45:27<502:32:41,  3.40s/it]
  6%|▋         | 36805/569592 [5:45:31<497:29:27,  3.36s/it]
                                                            

  6%|▋         | 36805/569592 [5:45:31<497:29:27,  3.36s/it]
  6%|▋         | 36806/569592 [5:45:34<503:46:09,  3.40s/it]
                                                            

  6%|▋         | 36806/569592 [5:45:34<503:46:09,  3.40s/it]
  6%|▋         | 36807/569592 [5:45:39<584:39:44,  3.95s/it]
                                                            

  6%|▋         | 36807/569592 [5:45:39<584:39:44,  3.95s/it]
  6%|▋         | 36808/569592 [5:45:40<448:19:39,  3.03s/it]
                                                            

  6%|▋         | 36808/569592 [5:45:40<448:19:39,  3.03s/it]
  6%|▋         | 36809/569592 [5:45:43<454:34:18,  3.07s/it]
                                                            

  6%|▋         | 36809/569592 [5:45:44<454:34:18,  3.07s/it]
  6%|▋         | 36810/569592 [5:45:47<477:53:02,  3.23s/it]
                                                            

  6%|▋         | 36810/569592 [5:45:47<477:53:02,  3.23s/it]
  6%|▋         | 36811/569592 [5:45:52<547:15:57,  3.70s/it]
                                                            

  6%|▋         | 36811/569592 [5:45:52<547:15:57,  3.70s/it]
  6%|▋         | 36812/569592 [5:45:56<555:10:34,  3.75s/it]
                                                            

  6%|▋         | 36812/569592 [5:45:56<555:10:34,  3.75s/it]
  6%|▋         | 36813/569592 [5:46:00<593:08:15,  4.01s/it]
                                                            

  6%|▋         | 36813/569592 [5:46:00<593:08:15,  4.01s/it]
  6%|▋         | 36814/569592 [5:46:01<453:29:22,  3.06s/it]
                                                            

  6%|▋         | 36814/569592 [5:46:01<453:29:22,  3.06s/it]
  6%|▋         | 36815/569592 [5:46:05<484:02:20,  3.27s/it]
                                                            

  6%|▋         | 36815/569592 [5:46:05<484:02:20,  3.27s/it]
  6%|▋         | 36816/569592 [5:46:08<473:05:38,  3.20s/it]
                                                            

  6%|▋         | 36816/569592 [5:46:08<473:05:38,  3.20s/it]
  6%|▋         | 36817/569592 [5:46:12<498:04:38,  3.37s/it]
                                                            

  6%|▋         | 36817/569592 [5:46:12<498:04:38,  3.37s/it]
  6%|▋         | 36818/569592 [5:46:15<502:38:54,  3.40s/it]
                                                            

  6%|▋         | 36818/569592 [5:46:15<502:38:54,  3.40s/it]
  6%|▋         | 36819/569592 [5:46:18<495:13:36,  3.35s/it]
                                                            

  6%|▋         | 36819/569592 [5:46:18<495:13:36,  3.35s/it]
  6%|▋         | 36820/569592 [5:46:23<559:37:32,  3.78s/it]
                                                            

  6%|▋         | 36820/569592 [5:46:23<559:37:32,  3.78s/it]
  6%|▋         | 36821/569592 [5:46:24<431:53:07,  2.92s/it]
                                                            

  6%|▋         | 36821/569592 [5:46:24<431:53:07,  2.92s/it]
  6%|▋         | 36822/569592 [5:46:27<446:12:49,  3.02s/it]
                                                            

  6%|▋         | 36822/569592 [5:46:27<446:12:49,  3.02s/it]
  6%|▋         | 36823/569592 [5:46:33<566:29:22,  3.83s/it]
                                                            

  6%|▋         | 36823/569592 [5:46:33<566:29:22,  3.83s/it]
  6%|▋         | 36824/569592 [5:46:37<549:22:23,  3.71s/it]
                                                            

  6%|▋         | 36824/569592 [5:46:37<549:22:23,  3.71s/it]
  6%|▋         | 36825/569592 [5:46:37<422:46:58,  2.86s/it]
                                                            

  6%|▋         | 36825/569592 [5:46:37<422:46:58,  2.86s/it]
  6%|▋         | 36826/569592 [5:46:38<337:34:43,  2.28s/it]
                                                            

  6%|▋         | 36826/569592 [5:46:38<337:34:43,  2.28s/it]
  6%|▋         | 36827/569592 [5:46:44<465:37:21,  3.15s/it]
                                                            

  6%|▋         | 36827/569592 [5:46:44<465:37:21,  3.15s/it]
  6%|▋         | 36828/569592 [5:46:48<513:15:41,  3.47s/it]
                                                            

  6%|▋         | 36828/569592 [5:46:48<513:15:41,  3.47s/it]
  6%|▋         | 36829/569592 [5:46:51<496:37:11,  3.36s/it]
                                                            

  6%|▋         | 36829/569592 [5:46:51<496:37:11,  3.36s/it]
  6%|▋         | 36830/569592 [5:46:55<552:35:50,  3.73s/it]
                                                            

  6%|▋         | 36830/569592 [5:46:55<552:35:50,  3.73s/it]
  6%|▋         | 36831/569592 [5:46:59<552:02:41,  3.73s/it]
                                                            

  6%|▋         | 36831/569592 [5:46:59<552:02:41,  3.73s/it]
  6%|▋         | 36832/569592 [5:47:02<533:04:42,  3.60s/it]
                                                            

  6%|▋         | 36832/569592 [5:47:03<533:04:42,  3.60s/it]
  6%|▋         | 36833/569592 [5:47:03<415:36:35,  2.81s/it]
                                                            

  6%|▋         | 36833/569592 [5:47:03<415:36:35,  2.81s/it]
  6%|▋         | 36834/569592 [5:47:04<3/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (91657005 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
34:25:22,  2.26s/it]
                                                            

  6%|▋         | 36834/569592 [5:47:04<334:25:22,  2.26s/it]
  6%|▋         | 36835/569592 [5:47:08<410:22:29,  2.77s/it]
                                                            

  6%|▋         | 36835/569592 [5:47:08<410:22:29,  2.77s/it]
  6%|▋         | 36836/569592 [5:47:12<453:28:04,  3.06s/it]
                                                            

  6%|▋         | 36836/569592 [5:47:12<453:28:04,  3.06s/it]
  6%|▋         | 36837/569592 [5:47:13<360:12:58,  2.43s/it]
                                                            

  6%|▋         | 36837/569592 [5:47:13<360:12:58,  2.43s/it]
  6%|▋         | 36838/569592 [5:47:17<435:34:25,  2.94s/it]
                                                            

  6%|▋         | 36838/569592 [5:47:17<435:34:25,  2.94s/it]
  6%|▋         | 36839/569592 [5:47:21<460:46:24,  3.11s/it]
                                                            

  6%|▋         | 36839/569592 [5:47:21<460:46:24,  3.11s/it]
  6%|▋         | 36840/569592 [5:47:24<465:20:45,  3.14s/it]
                                                            

  6%|▋         | 36840/569592 [5:47:24<465:20:45,  3.14s/it]
  6%|▋         | 36841/569592 [5:47:29<533:54:28,  3.61s/it]
                                                            

  6%|▋         | 36841/569592 [5:47:29<533:54:28,  3.61s/it]
  6%|▋         | 36842/569592 [5:47:30<413:27:28,  2.79s/it]
                                                            

  6%|▋         | 36842/569592 [5:47:30<413:27:28,  2.79s/it]
  6%|▋         | 36843/569592 [5:47:30<330:49:50,  2.24s/it]
                                                            

  6%|▋         | 36843/569592 [5:47:31<330:49:50,  2.24s/it]
  6%|▋         | 36844/569592 [5:47:31<274:23:27,  1.85s/it]
                                                            

  6%|▋         | 36844/569592 [5:47:31<274:23:27,  1.85s/it]
  6%|▋         | 36845/569592 [5:47:35<357:49:24,  2.42s/it]
                                                            

  6%|▋         | 36845/569592 [5:47:35<357:49:24,  2.42s/it]
  6%|▋         | 36846/569592 [5:47:40<476:43:28,  3.22s/it]
                                                            

  6%|▋         | 36846/569592 [5:47:40<476:43:28,  3.22s/it]
  6%|▋         | 36847/569592 [5:47:41<375:11:14,  2.54s/it]
                                                            

  6%|▋         | 36847/569592 [5:47:41<375:11:14,  2.54s/it]
  6%|▋         | 36848/569592 [5:47:44<403:49:31,  2.73s/it]
                                                            

  6%|▋         | 36848/569592 [5:47:44<403:49:31,  2.73s/it]
  6%|▋         | 36849/569592 [5:47:48<434:01:46,  2.93s/it]
                                                            

  6%|▋         | 36849/569592 [5:47:48<434:01:46,  2.93s/it]
  6%|▋         | 36850/569592 [5:47:49<349:35:12,  2.36s/it]
                                                            

  6%|▋         | 36850/569592 [5:47:49<349:35:12,  2.36s/it]
  6%|▋         | 36851/569592 [5:47:53<439:20:40,  2.97s/it]
                                                            

  6%|▋         | 36851/569592 [5:47:53<439:20:40,  2.97s/it]
  6%|▋         | 36852/569592 [5:47:57<474:50:29,  3.21s/it]
                                                            

  6%|▋         | 36852/569592 [5:47:57<474:50:29,  3.21s/it]
  6%|▋         | 36853/569592 [5:48:01<497:25:32,  3.36s/it]
                                                            

  6%|▋         | 36853/569592 [5:48:01<497:25:32,  3.36s/it]
  6%|▋         | 36854/569592 [5:48:02<388:09:36,  2.62s/it]
                                                            

  6%|▋         | 36854/569592 [5:48:02<388:09:36,  2.62s/it]
  6%|▋         | 36855/569592 [5:48:03<313:48:39,  2.12s/it]
                                                            

  6%|▋         | 36855/569592 [5:48:03<313:48:39,  2.12s/it]
  6%|▋         | 36856/569592 [5:48:04<269:23:45,  1.82s/it]
                                                            

  6%|▋         | 36856/569592 [5:48:04<269:23:45,  1.82s/it]
  6%|▋         | 36857/569592 [5:48:07<348:38:42,  2.36s/it]
                                                            

  6%|▋         | 36857/569592 [5:48:07<348:38:42,  2.36s/it]
  6%|▋         | 36858/569592 [5:48:11<391:11:14,  2.64s/it]
                                                            

  6%|▋         | 36858/569592 [5:48:11<391:11:14,  2.64s/it]
  6%|▋         | 36859/569592 [5:48:12<315:19:17,  2.13s/it]
                                                            

  6%|▋         | 36859/569592 [5:48:12<315:19:17,  2.13s/it]
  6%|▋         | 36860/569592 [5:48:12<262:51:55,  1.78s/it]
                                                            

  6%|▋         | 36860/569592 [5:48:12<262:51:55,  1.78s/it]
  6%|▋         | 36861/569592 [5:48:16<340:16:44,  2.30s/it]
                                                            

  6%|▋         | 36861/569592 [5:48:16<340:16:44,  2.30s/it]
  6%|▋         | 36862/569592 [5:48:17<280:02:43,  1.89s/it]
                                                            

  6%|▋         | 36862/569592 [5:48:17<280:02:43,  1.89s/it]
  6%|▋         | 36863/569592 [5:48:18<237:34:58,  1.61s/it]
                                                            

  6%|▋         | 36863/569592 [5:48:18<237:34:58,  1.61s/it]
  6%|▋         | 36864/569592 [5:48:19<206:52:57,  1.40s/it]
                                                            

  6%|▋         | 36864/569592 [5:48:19<206:52:57,  1.40s/it]
  6%|▋         | 36865/569592 [5:48:20<219:35:32,  1.48s/it]
                                                            

  6%|▋         | 36865/569592 [5:48:20<219:35:32,  1.48s/it]
  6%|▋         | 36866/569592 [5:48:25<334:04:56,  2.26s/it]
                                                            

  6%|▋         | 36866/569592 [5:48:25<334:04:56,  2.26s/it]
  6%|▋         | 36867/569592 [5:48:26<278:03:25,  1.88s/it]
                                                            

  6%|▋         | 36867/569592 [5:48:26<278:03:25,  1.88s/it]
  6%|▋         | 36868/569592 [5:48:26<237:09:47,  1.60s/it]
                                                            

  6%|▋         | 36868/569592 [5:48:27<237:09:47,  1.60s/it]
  6%|▋         | 36869/569592 [5:48:31<351:42:54,  2.38s/it]
                                                            

  6%|▋         | 36869/569592 [5:48:31<351:42:54,  2.38s/it]
  6%|▋         | 36870/569592 [5:48:34<415:26:24,  2.81s/it]
                                                            

  6%|▋         | 36870/569592 [5:48:34<415:26:24,  2.81s/it]
  6%|▋         | 36871/569592 [5:48:38<442:12:57,  2.99s/it]
                                                            

  6%|▋         | 36871/569592 [5:48:38<442:12:57,  2.99s/it]
  6%|▋         | 36872/569592 [5:48:41<465:18:40,  3.14s/it]
                                                            

  6%|▋         | 36872/569592 [5:48:41<465:18:40,  3.14s/it]
  6%|▋         | 36873/569592 [5:48:43<398:41:57,  2.69s/it]
                                                            

  6%|▋         | 36873/569592 [5:48:43<398:41:57,  2.69s/it]
  6%|▋         | 36874/569592 [5:48:46<423:31:45,  2.86s/it]
                                                            

  6%|▋         | 36874/569592 [5:48:46<423:31:45,  2.86s/it]
  6%|▋         | 36875/569592 [5:48:50<452:48:26,  3.06s/it]
                                                            

  6%|▋         | 36875/569592 [5:48:50<452:48:26,  3.06s/it]
  6%|▋         | 36876/569592 [5:48:53<466:43:00,  3.15s/it]
                                                            

  6%|▋         | 36876/569592 [5:48:53<466:43:00,  3.15s/it]
  6%|▋         | 36877/569592 [5:48:54<370:36:49,  2.50s/it]
                                                            

  6%|▋         | 36877/569592 [5:48:54<370:36:49,  2.50s/it]
  6%|▋         | 36878/569592 [5:48:59<474:12:28,  3.20s/it]
                                                            

  6%|▋         | 36878/569592 [5:48:59<474:12:28,  3.20s/it]
  6%|▋         | 36879/569592 [5:49:00<375:33:30,  2.54s/it]
                                                            

  6%|▋         | 36879/569592 [5:49:00<375:33:30,  2.54s/it]
  6%|▋         | 36880/569592 [5:49:01<305:49:29,  2.07s/it]
                                                            

  6%|▋         | 36880/569592 [5:49:01<305:49:29,  2.07s/it]
  6%|▋         | 36881/569592 [5:49:04<347:48:07,  2.35s/it]
                                                            

  6%|▋         | 36881/569592 [5:49:04<347:48:07,  2.35s/it]
  6%|▋         | 36882/569592 [5:49:08<404:09:45,  2.73s/it]
                                                            

  6%|▋         | 36882/569592 [5:49:08<404:09:45,  2.73s/it]
  6%|▋         | 36883/569592 [5:49:09<325:48:22,  2.20s/it]
                                                            

  6%|▋         | 36883/569592 [5:49:09<325:48:22,  2.20s/it]
  6%|▋         | 36884/569592 [5:49:12<376:57:20,  2.55s/it]
                                                            

  6%|▋         | 36884/569592 [5:49:12<376:57:20,  2.55s/it]
  6%|▋         | 36885/569592 [5:49:14<343:25:36,  2.32s/it]
                                                            

  6%|▋         | 36885/569592 [5:49:14<343:25:36,  2.32s/it]
  6%|▋         | 36886/569592 [5:49:16<352:07:40,  2.38s/it]
                                                            

  6%|▋         | 36886/569592 [5:49:16<352:07:40,  2.38s/it]
  6%|▋         | 36887/569592 [5:49:17<296:46:39,  2.01s/it]
                                                            

  6%|▋         | 36887/569592 [5:49:17<296:46:39,  2.01s/it]
  6%|▋         | 36888/569592 [5:49:21<365:45:49,  2.47s/it]
                                                            

  6%|▋         | 36888/569592 [5:49:21<365:45:49,  2.47s/it]
  6%|▋         | 36889/569592 [5:49:26<475:01:42,  3.21s/it]
                                                            

  6%|▋         | 36889/569592 [5:49:26<475:01:42,  3.21s/it]
  6%|▋         | 36890/569592 [5:49:28<412:25:03,  2.79s/it]
                                                            

  6%|▋         | 36890/569592 [5:49:28<412:25:03,  2.79s/it]
  6%|▋         | 36891/569592 [5:49:29<347:25:16,  2.35s/it]
                                                            

  6%|▋         | 36891/569592 [5:49:29<347:25:16,  2.35s/it]
  6%|▋         | 36892/569592 [5:49:34<454:10:28,  3.07s/it]
                                                            

  6%|▋         | 36892/569592 [5:49:34<454:10:28,  3.07s/it]
  6%|▋         | 36893/569592 [5:49:35<360:21:39,  2.44s/it]
                                                            

  6%|▋         | 36893/569592 [5:49:35<360:21:39,  2.44s/it]
  6%|▋         | 36894/569592 [5:49:38<421:04:58,  2.85s/it]
                                                            

  6%|▋         | 36894/569592 [5:49:39<421:04:58,  2.85s/it]
  6%|▋         | 36895/569592 [5:49:42<452:59:12,  3.06s/it]
                                                            

  6%|▋         | 36895/569592 [5:49:42<452:59:12,  3.06s/it]
  6%|▋         | 36896/569592 [5:49:46<475:25:19,  3.21s/it]
                                                            

  6%|▋         | 36896/569592 [5:49:46<475:25:19,  3.21s/it]
  6%|▋         | 36897/569592 [5:49:49<491:16:50,  3.32s/it]
                                                            

  6%|▋         | 36897/569592 [5:49:49<491:16:50,  3.32s/it]
  6%|▋         | 36898/569592 [5:49:53<505:05:58,  3.41s/it]
                                                            

  6%|▋         | 36898/569592 [5:49:53<505:05:58,  3.41s/it]
  6%|▋         | 36899/569592 [5:49:54<394:47:16,  2.67s/it]
                                                            

  6%|▋         | 36899/569592 [5:49:54<394:47:16,  2.67s/it]
  6%|▋         | 36900/569592 [5:49:57<420:49:08,  2.84s/it]
                                                            

  6%|▋         | 36900/569592 [5:49:57<420:49:08,  2.84s/it]
  6%|▋         | 36901/569592 [5:50:00<445:20:21,  3.01s/it]
                                                            

  6%|▋         | 36901/569592 [5:50:00<445:20:21,  3.01s/it]
  6%|▋         | 36902/569592 [5:50:04<453:39:39,  3.07s/it]
                                                            

  6%|▋         | 36902/569592 [5:50:04<453:39:39,  3.07s/it]
  6%|▋         | 36903/569592 [5:50:07<452:21:32,  3.06s/it]
                                                            

  6%|▋         | 36903/569592 [5:50:07<452:21:32,  3.06s/it]
  6%|▋         | 36904/569592 [5:50:08<356:44:28,  2.41s/it]
                                                            

  6%|▋         | 36904/569592 [5:50:08<356:44:28,  2.41s/it]
  6%|▋         | 36905/569592 [5:50:08<292:00:51,  1.97s/it]
                                                            

  6%|▋         | 36905/569592 [5:50:09<292:00:51,  1.97s/it]
  6%|▋         | 36906/569592 [5:50:12<364:51:50,  2.47s/it]
                                                            

  6%|▋         | 36906/569592 [5:50:12<364:51:50,  2.47s/it]
  6%|▋         | 36907/569592 [5:50:13<297:26:12,  2.01s/it]
                                                            

  6%|▋         | 36907/569592 [5:50:13<297:26:12,  2.01s/it]
  6%|▋         | 36908/569592 [5:50:18<436:57:32,  2.95s/it]
                                                            

  6%|▋         | 36908/569592 [5:50:18<436:57:32,  2.95s/it]
  6%|▋         | 36909/569592 [5:50:22<477:28:32,  3.23s/it]
                                                            

  6%|▋         | 36909/569592 [5:50:22<477:28:32,  3.23s/it]
  6%|▋         | 36910/569592 [5:50:23<375:26:58,  2.54s/it]
                                                            

  6%|▋         | 36910/569592 [5:50:23<375:26:58,  2.54s/it]
  6%|▋         | 36911/569592 [5:50:24<304:36:59,  2.06s/it]
                                                            

  6%|▋         | 36911/569592 [5:50:24<304:36:59,  2.06s/it]
  6%|▋         | 36912/569592 [5:50:29<416:22:35,  2.81s/it]
                                                            

  6%|▋         | 36912/569592 [5:50:29<416:22:35,  2.81s/it]
  6%|▋         | 36913/569592 [5:50:32<463:00:11,  3.13s/it]
                                                            

  6%|▋         | 36913/569592 [5:50:32<463:00:11,  3.13s/it]
  6%|▋         | 36914/569592 [5:50:33<365:56:51,  2.47s/it]
                                                            

  6%|▋         | 36914/569592 [5:50:33<365:56:51,  2.47s/it]
  6%|▋         | 36915/569592 [5:50:34<297:45:58,  2.01s/it]
                                                            

  6%|▋         | 36915/569592 [5:50:34<297:45:58,  2.01s/it]
  6%|▋         | 36916/569592 [5:50:38<360:52:31,  2.44s/it]
                                                            

  6%|▋         | 36916/569592 [5:50:38<360:52:31,  2.44s/it]
  6%|▋         | 36917/569592 [5:50:41<418:19:40,  2.83s/it]
                                                            

  6%|▋         | 36917/569592 [5:50:41<418:19:40,  2.83s/it]
  6%|▋         | 36918/569592 [5:50:45<444:45:38,  3.01s/it]
                                                            

  6%|▋         | 36918/569592 [5:50:45<444:45:38,  3.01s/it]
  6%|▋         | 36919/569592 [5:50:48<454:04:53,  3.07s/it]
                                                            

  6%|▋         | 36919/569592 [5:50:48<454:04:53,  3.07s/it]
  6%|▋         | 36920/569592 [5:50:53<522:59:39,  3.53s/it]
                                                            

  6%|▋         | 36920/569592 [5:50:53<522:59:39,  3.53s/it]
  6%|▋         | 36921/569592 [5:50:57<574:03:42,  3.88s/it]
                                                            

  6%|▋         | 36921/569592 [5:50:57<574:03:42,  3.88s/it]
  6%|▋         | 36922/569592 [5:51:00<538:09:24,  3.64s/it]
                                                            

  6%|▋         | 36922/569592 [5:51:00<538:09:24,  3.64s/it]
  6%|▋         | 36923/569592 [5:51:01<415:42:20,  2.81s/it]
                                                            

  6%|▋         | 36923/569592 [5:51:01<415:42:20,  2.81s/it]
  6%|▋         | 36924/569592 [5:51:06<510:43:49,  3.45s/it]
                                                            

  6%|▋         | 36924/569592 [5:51:06<510:43:49,  3.45s/it]
  6%|▋         | 36925/569592 [5:51:10<525:57:05,  3.55s/it]
                                                            

  6%|▋         | 36925/569592 [5:51:10<525:57:05,  3.55s/it]
  6%|▋         | 36926/569592 [5:51:13<518:04:09,  3.50s/it]
                                                            

  6%|▋         | 36926/569592 [5:51:13<518:04:09,  3.50s/it]
  6%|▋         | 36927/569592 [5:51:18<553:26:41,  3.74s/it]
                                                            

  6%|▋         | 36927/569592 [5:51:18<553:26:41,  3.74s/it]
  6%|▋         | 36928/569592 [5:51:21<549:08:52,  3.71s/it]
                                                            

  6%|▋         | 36928/569592 [5:51:21<549:08:52,  3.71s/it]
  6%|▋         | 36929/569592 [5:51:24<521:27:33,  3.52s/it]
                                                            

  6%|▋         | 36929/569592 [5:51:24<521:27:33,  3.52s/it]
  6%|▋         | 36930/569592 [5:51:28<523:59:03,  3.54s/it]
                                                            

  6%|▋         | 36930/569592 [5:51:28<523:59:03,  3.54s/it]
  6%|▋         | 36931/569592 [5:51:33<572:06:12,  3.87s/it]
                                                            

  6%|▋         | 36931/569592 [5:51:33<572:06:12,  3.87s/it]
  6%|▋         | 36932/569592 [5:51:38<614:55:33,  4.16s/it]
                                                            

  6%|▋         | 36932/569592 [5:51:38<614:55:33,  4.16s/it]
  6%|▋         | 36933/569592 [5:51:42<634:53:49,  4.29s/it]
                                                            

  6%|▋         | 36933/569592 [5:51:42<634:53:49,  4.29s/it]
  6%|▋         | 36934/569592 [5:51:43<487:47:24,  3.30s/it]
                                                            

  6%|▋         | 36934/569592 [5:51:43<487:47:24,  3.30s/it]
  6%|▋         | 36935/569592 [5:51:46<491:52:23,  3.32s/it]
                                                            

  6%|▋         | 36935/569592 [5:51:47<491:52:23,  3.32s/it]
  6%|▋         | 36936/569592 [5:51:51<558:01:49,  3.77s/it]
                                                            

  6%|▋         | 36936/569592 [5:51:51<558:01:49,  3.77s/it]
  6%|▋         | 36937/569592 [5:51:52<431:10:03,  2.91s/it]
                                                            

  6%|▋         | 36937/569592 [5:51:52<431:10:03,  2.91s/it]
  6%|▋         | 36938/569592 [5:51:56<467:46:09,  3.16s/it]
                                                            

  6%|▋         | 36938/569592 [5:51:56<467:46:09,  3.16s/it]
  6%|▋         | 36939/569592 [5:51:59<478:53:26,  3.24s/it]
                                                            

  6%|▋         | 36939/569592 [5:51:59<478:53:26,  3.24s/it]
  6%|▋         | 36940/569592 [5:52:03<476:38:04,  3.22s/it]
                                                            

  6%|▋         | 36940/569592 [5:52:03<476:38:04,  3.22s/it]
  6%|▋         | 36941/569592 [5:52:06<485:25:12,  3.28s/it]
                                                            

  6%|▋         | 36941/569592 [5:52:06<485:25:12,  3.28s/it]
  6%|▋         | 36942/569592 [5:52:09<476:47:06,  3.22s/it]
                                                            

  6%|▋         | 36942/569592 [5:52:09<476:47:06,  3.22s/it]
  6%|▋         | 36943/569592 [5:52:12<476:30:55,  3.22s/it]
                                                            

  6%|▋         | 36943/569592 [5:52:12<476:30:55,  3.22s/it]
  6%|▋         | 36944/569592 [5:52:16<498:08:38,  3.37s/it]
                                                            

  6%|▋         | 36944/569592 [5:52:16<498:08:38,  3.37s/it]
  6%|▋         | 36945/569592 [5:52:19<497:46:48,  3.36s/it]
                                                            

  6%|▋         | 36945/569592 [5:52:19<497:46:48,  3.36s/it]
  6%|▋         | 36946/569592 [5:52:23<498:30:27,  3.37s/it]
                                                            

  6%|▋         | 36946/569592 [5:52:23<498:30:27,  3.37s/it]
  6%|▋         | 36947/569592 [5:52:26<495:18:44,  3.35s/it]
                                                            

  6%|▋         | 36947/569592 [5:52:26<495:18:44,  3.35s/it]
  6%|▋         | 36948/569592 [5:52:30<521:22:50,  3.52s/it]
                                                            

  6%|▋         | 36948/569592 [5:52:30<521:22:50,  3.52s/it]
  6%|▋         | 36949/569592 [5:52:34<543:53:18,  3.68s/it]
                                                            

  6%|▋         | 36949/569592 [5:52:34<543:53:18,  3.68s/it]
  6%|▋         | 36950/569592 [5:52:37<529:16:51,  3.58s/it]
                                                            

  6%|▋         | 36950/569592 [5:52:37<529:16:51,  3.58s/it]
  6%|▋         | 36951/569592 [5:52:41<532:25:36,  3.60s/it]
                                                            

  6%|▋         | 36951/569592 [5:52:41<532:25:36,  3.60s/it]
  6%|▋         | 36952/569592 [5:52:44<521:14:40,  3.52s/it]
                                                            

  6%|▋         | 36952/569592 [5:52:44<521:14:40,  3.52s/it]
  6%|▋         | 36953/569592 [5:52:48<512:55:48,  3.47s/it]
                                                            

  6%|▋         | 36953/569592 [5:52:48<512:55:48,  3.47s/it]
  6%|▋         | 36954/569592 [5:52:51<510:13:08,  3.45s/it]
                                                            

  6%|▋         | 36954/569592 [5:52:51<510:13:08,  3.45s/it]
  6%|▋         | 36955/569592 [5:52:56<554:19:12,  3.75s/it]
                                                            

  6%|▋         | 36955/569592 [5:52:56<554:19:12,  3.75s/it]
  6%|▋         | 36956/569592 [5:52:59<556:36:51,  3.76s/it]
                                                            

  6%|▋         | 36956/569592 [5:52:59<556:36:51,  3.76s/it]
  6%|▋         | 36957/569592 [5:53:00<429:41:22,  2.90s/it]
                                                            

  6%|▋         | 36957/569592 [5:53:00<429:41:22,  2.90s/it]
  6%|▋         | 36958/569592 [5:53:04<465:16:31,  3.14s/it]
                                                            

  6%|▋         | 36958/569592 [5:53:04<465:16:31,  3.14s/it]
  6%|▋         | 36959/569592 [5:53:08<488:25:03,  3.30s/it]
                                                            

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  warnings.warn(
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  6%|▋         | 37000/569592 [5:54:48<302:24:00,  2.04s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-37000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-37000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-37000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-37000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-37000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-37000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-36000] due to args.save_total_limit

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  warnings.warn(
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  7%|▋         | 37066/569592 [6:00:14<334:34:/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (104594490 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
27,  2.26s/it]
                                                            

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  7%|▋         | 37077/569/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98911692 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
592 [6:00:52<450:21:54,  3.04s/it]
                                                            

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                                 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                           

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  7%|▋         | 37158/569592 [6:/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98911692 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
04:35<476:59:12,  3.23s/it]
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                                                         /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
   

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  7%|▋        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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                     /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (96735300 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                       

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                             /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (108885000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                               

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                                 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                           

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  7%|▋         | 37465/569592 [6:18:59<485:44:56,  3.29s/it]
  7%|▋         | 37466/569592 [6:19:02<492:03:40,  3.33s/it]
                                                            

  7%|▋         | 37466/569592 [6:19:02<492:03:40,  3.33s/it]
  7%|▋         | 37467/569592 [6:19:03<386:49:35,  2.62s/it]
                                                            

  7%|▋         | 37467/569592 [6:19:03<386:49:35,  2.62s/it]
  7%|▋         | 37468/569592 [6:19:07<438:43:08,  2.97s/it]
                                                            

  7%|▋         | 37468/569592 [6:19:07<438:43:08,  2.97s/it]
  7%|▋         | 37469/569592 [6:19:08<347:52:52,  2.35s/it]
                                                            

  7%|▋         | 37469/569592 [6:19:08<347:52:52,  2.35s/it]
  7%|▋         | 37470/569592 [6:19:12<412:07:39,  2.79s/it]
                                                            

  7%|▋         | 37470/569592 [6:19:12<412:07:39,  2.79s/it]
  7%|▋         | 37471/569592 [6:19:13<330:12:54,  2.23s/it]
                                                            

  7%|▋         | 37471/569592 [6:19:13<330:12:54,  2.23s/it]
  7%|▋         | 37472/569592 [6:19:14<273:22:40,  1.85s/it]
                                                            

  7%|▋         | 37472/569592 [6:19:14<273:22:40,  1.85s/it]
  7%|▋         | 37473/569592 [6:19:15<240:22:59,  1.63s/it]
                                                            

  7%|▋         | 37473/569592 [6:19:15<240:22:59,  1.63s/it]
  7%|▋         | 37474/569592 [6:19:19<372:57:49,  2.52s/it]
                                                            

  7%|▋         | 37474/569592 [6:19:19<372:57:49,  2.52s/it]
  7%|▋         | 37475/569592 [6:19:20<307:37:42,  2.08s/it]
                                                            

  7%|▋         | 37475/569592 [6:19:20<307:37:42,  2.08s/it]
  7%|▋         | 37476/569592 [6:19:24<375:35:10,  2.54s/it]
                                                            

  7%|▋         | 37476/569592 [6:19:24<375:35:10,  2.54s/it]
  7%|▋         | 37477/569592 [6:19:28<422:01:29,  2.86s/it]
                                                            

  7%|▋         | 37477/569592 [6:19:28<422:01:29,  2.86s/it]
  7%|▋         | 37478/569592 [6:19:28<338:13:32,  2.29s/it]
                                                            

  7%|▋         | 37478/569592 [6:19:29<338:13:32,  2.29s/it]
  7%|▋         | 37479/569592 [6:19:29<278:43:57,  1.89s/it]
                                                            

  7%|▋         | 37479/569592 [6:19:29<278:43:57,  1.89s/it]
  7%|▋         | 37480/569592 [6:19:33<363:35:23,  2.46s/it]
                                                            

  7%|▋         | 37480/569592 [6:19:33<363:35:23,  2.46s/it]
  7%|▋         | 37481/569592 [6:19:37<413:04:37,  2.79s/it]
                                                            

  7%|▋         | 37481/569592 [6:19:37<413:04:37,  2.79s/it]
  7%|▋         | 37482/569592 [6:19:40<439:27:56,  2.97s/it]
                                                            

  7%|▋         | 37482/569592 [6:19:40<439:27:56,  2.97s/it]
  7%|▋         | 37483/569592 [6:19:43<450:02:24,  3.04s/it]
                                                            

  7%|▋         | 37483/569592 [6:19:43<450:02:24,  3.04s/it]
  7%|▋         | 37484/569592 [6:19:47<463:14:11,  3.13s/it]
                                                            

  7%|▋         | 37484/569592 [6:19:47<463:14:11,  3.13s/it]
  7%|▋         | 37485/569592 [6:19:51<501:55:35,  3.40s/it]
                                                            

  7%|▋         | 37485/569592 [6:19:51<501:55:35,  3.40s/it]
  7%|▋         | 37486/569592 [6:19:55<529:58:05,  3.59s/it]
                                                            

  7%|▋         | 37486/569592 [6:19:55<529:58:05,  3.59s/it]
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  7%|▋         | 37487/569592 [6:19:58<512:44:18,  3.47s/it]
  7%|▋         | 37488/569592 [6:19:59<399:42:23,  2.70s/it]
                                                            

  7%|▋         | 37488/569592 [6:19:59<399:42:23,  2.70s/it]
  7%|▋         | 37489/569592 [6:20:02<430:55:15,  2.92s/it]
                                                            

  7%|▋         | 37489/569592 [6:20:02<430:55:15,  2.92s/it]
  7%|▋         | 37490/569592 [6:20:06<470:49:18,  3.19s/it]
                                                            

  7%|▋         | 37490/569592 [6:20:06<470:49:18,  3.19s/it]
  7%|▋         | 37491/569592 [6:20:07<372:10:06,  2.52s/it]
                                                            

  7%|▋         | 37491/569592 [6:20:07<372:10:06,  2.52s/it]
  7%|▋         | 37492/569592 [6:20:13<518:42:24,  3.51s/it]
                                                            

  7%|▋         | 37492/569592 [6:20:13<518:42:24,  3.51s/it]
  7%|▋         | 37493/569592 [6:20:16<500:51:28,  3.39s/it]
                                                            

  7%|▋         | 37493/569592 [6:20:16<500:51:28,  3.39s/it]
  7%|▋         | 37494/569592 [6:20:17<390:39:55,  2.64s/it]
                                                            

  7%|▋         | 37494/569592 [6:20:17<390:39:55,  2.64s/it]
  7%|▋         | 37495/569592 [6:20:18<314:40:12,  2.13s/it]
                                                            

  7%|▋         | 37495/569592 [6:20:18<314:40:12,  2.13s/it]
  7%|▋         | 37496/569592 [6:20:19<263:41:11,  1.78s/it]
                                                            

  7%|▋         | 37496/569592 [6:20:19<263:41:11,  1.78s/it]
  7%|▋         | 37497/569592 [6:20:22<328:37:45,  2.22s/it]
                                                            

  7%|▋         | 37497/569592 [6:20:22<328:37:45,  2.22s/it]
  7%|▋         | 37498/569592 [6:20:26<403:19:12,  2.73s/it]
                                                            

  7%|▋         | 37498/569592 [6:20:26<403:19:12,  2.73s/it]
  7%|▋         | 37499/569592 [6:20:29<435:41:38,  2.95s/it]
                                                            

  7%|▋         | 37499/569592 [6:20:29<435:41:38,  2.95s/it]
  7%|▋         | 37500/569592 [6:20:33<448:15:32,  3.03s/it]
                                                            

  7%|▋         | 37500/569592 [6:20:33<448:15:32,  3.03s/it]
  7%|▋         | 37501/569592 [6:20:36<466:41:02,  3.16s/it]
                                                            

  7%|▋         | 37501/569592 [6:20:36<466:41:02,  3.16s/it]
  7%|▋         | 37502/569592 [6:20:40<487:55:34,  3.30s/it]
                                                            

  7%|▋         | 37502/569592 [6:20:40<487:55:34,  3.30s/it]
  7%|▋         | 37503/569592 [6:20:43<506:07:46,  3.42s/it]
                                                            

  7%|▋         | 37503/569592 [6:20:43<506:07:46,  3.42s/it]
  7%|▋         | 37504/569592 [6:20:47<503:18:31,  3.41s/it]
                                                            

  7%|▋         | 37504/569592 [6:20:47<503:18:31,  3.41s/it]
  7%|▋         | 37505/569592 [6:20:48<393:54:47,  2.67s/it]
                                                            

  7%|▋         | 37505/569592 [6:20:48<393:54:47,  2.67s/it]
  7%|▋         | 37506/569592 [6:20:53<492:02:32,  3.33s/it]
                                                            

  7%|▋         | 37506/569592 [6:20:53<492:02:32,  3.33s/it]
  7%|▋         | 37507/569592 [6:20:54<388:12:06,  2.63s/it]
                                                            

  7%|▋         | 37507/569592 [6:20:54<388:12:06,  2.63s/it]
  7%|▋         | 37508/569592 [6:20:57<424:29:28,  2.87s/it]
                                                            

  7%|▋         | 37508/569592 [6:20:57<424:29:28,  2.87s/it]
  7%|▋         | 37509/569592 [6:21:00<448:17:18,  3.03s/it]
                                                            

  7%|▋         | 37509/569592 [6:21:01<448:17:18,  3.03s/it]
  7%|▋         | 37510/569592 [6:21:04<453:00:46,  3.07s/it]
                                                            

  7%|▋         | 37510/569592 [6:21:04<453:00:46,  3.07s/it]
  7%|▋         | 37511/569592 [6:21:07<451:54:51,  3.06s/it]
                                                            

  7%|▋         | 37511/569592 [6:21:07<451:54:51,  3.06s/it]
  7%|▋         | 37512/569592 [6:21:10<459:04:55,  3.11s/it]
                                                            

  7%|▋         | 37512/569592 [6:21:10<459:04:55,  3.11s/it]
  7%|▋         | 37513/569592 [6:21:13<462:02:13,  3.13s/it]
                                                            

  7%|▋         | 37513/569592 [6:21:13<462:02:13,  3.13s/it]
  7%|▋         | 37514/569592 [6:21:16<467:16:33,  3.16s/it]
                                                            

  7%|▋         | 37514/569592 [6:21:16<467:16:33,  3.16s/it]
  7%|▋         | 37515/569592 [6:21:20<498:04:40,  3.37s/it]
                                                            

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  7%|▋         | 37516/569592 [6:21:21<390:39:30,  2.64s/it]
                                                            

  7%|▋         | 37516/569592 [6:21:21<390:39:30,  2.64s/it]
  7%|▋         | 37517/569592 [6:21:25<433:05:52,  2.93s/it]
                                                            

  7%|▋         | 37517/569592 [6:21:25<433:05:52,  2.93s/it]
  7%|▋         | 37518/569592 [6:21:30<516:17:41,  3.49s/it]
                                                            

  7%|▋         | 37518/569592 [6:21:30<516:17:41,  3.49s/it]
  7%|▋         | 37519/569592 [6:21:33<516:03:27,  3.49s/it]
                                                            

  7%|▋         | 37519/569592 [6:21:33<516:03:27,  3.49s/it]
  7%|▋         | 37520/569592 [6:21:36<514:58:22,  3.48s/it]
                                                            

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  7%|▋         | 37522/569592 [6:21:43<515:46:53,  3.49s/it]
                                                            

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  7%|▋         | 37523/569592 [6:21:47<504:50:25,  3.42s/it]
                                                            

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  7%|▋         | 37524/569592 [6:21:50<490:14:21,  3.32s/it]
                                                            

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  7%|▋         | 37525/569592 [6:21:55<568:09:12,  3.84s/it]
                                                            

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  7%|▋         | 37526/569592 [6:21:58<554:18:24,  3.75s/it]
                                                            

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  7%|▋         | 37527/569592 [6:22:02<552:41:08,  3.74s/it]
                                                            

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  7%|▋         | 37528/569592 [6:22:05<526:56:46,  3.57s/it]
                                                            

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  7%|▋         | 37529/569592 [6:22:09<525:34:00,  3.56s/it]
                                                            

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  7%|▋         | 37530/569592 [6:22:12<515:17:30,  3.49s/it]
                                                            

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  7%|▋         | 37531/569592 [6:22:15<508:17:39,  3.44s/it]
                                                            

  7%|▋         | 37531/569592 [6:22:15<508:17:39,  3.44s/it]
  7%|▋         | 37532/569592 [6:22:16<397:28:55,  2.69s/it]
                                                            

  7%|▋         | 37532/569592 [6:22:16<397:28:55,  2.69s/it]
  7%|▋         | 37533/569592 [6:22:20<423:27:00,  2.87s/it]
                                                            

  7%|▋         | 37533/569592 [6:22:20<423:27:00,  2.87s/it]
  7%|▋         | 37534/569592 [6:22:24<471:49:39,  3.19s/it]
                                                            

  7%|▋         | 37534/569592 [6:22:24<471:49:39,  3.19s/it]
  7%|▋         | 37535/569592 [6:22:25<373:25:37,  2.53s/it]
                                                            

  7%|▋         | 37535/569592 [6:22:25<373:25:37,  2.53s/it]
  7%|▋         | 37536/569592 [6:22:28<404:37:53,  2.74s/it]
                                                            

  7%|▋         | 37536/569592 [6:22:28<404:37:53,  2.74s/it]
  7%|▋         | 37537/569592 [6:22:29<326:04:21,  2.21s/it]
                                                            

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  7%|▋         | 37538/569592 [6:22:34<454:24:12,  3.07s/it]
                                                            

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  7%|▋         | 37539/569592 [6:22:37<475:36:34,  3.22s/it]
                                                            

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  7%|▋         | 37540/569592 [6:22:41<487:58:46,  3.30s/it]
                                                            

  7%|▋         | 37540/569592 [6:22:41<487:58:46,  3.30s/it]
  7%|▋         | 37541/569592 [6:22:46<545:43:38,  3.69s/it]
                                                            

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  7%|▋         | 37542/569592 [6:22:49<534:20:05,  3.62s/it]
                                                            

  7%|▋         | 37542/569592 [6:22:49<534:20:05,  3.62s/it]
  7%|▋         | 37543/569592 [6:22:50<413:14:36,  2.80s/it]
                                                            

  7%|▋         | 37543/569592 [6:22:50<413:14:36,  2.80s/it]
  7%|▋         | 37544/569592 [6:22:51<329:06:44,  2.23s/it]
                                                            

  7%|▋         | 37544/569592 [6:22:51<329:06:44,  2.23s/it]
  7%|▋         | 37545/569592 [6:22:54<379:32:47,  2.57s/it]
                                                            

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  7%|▋         | 37546/569592 [6:22:55<310:05:53,  2.10s/it]
                                                            

  7%|▋         | 37546/569592 [6:22:55<310:05:53,  2.10s/it]
  7%|▋         | 37547/569592 [6:22:56<258:57:07,  1.75s/it]
                                                            

  7%|▋         | 37547/569592 [6:22:56<258:57:07,  1.75s/it]
  7%|▋         | 37548/569592 [6:23:00<343:22:06,  2.32s/it]
                                                            

  7%|▋         | 37548/569592 [6:23:00<343:22:06,  2.32s/it]
  7%|▋         | 37549/569592 [6:23:03<405:42:24,  2.75s/it]
                                                            

  7%|▋         | 37549/569592 [6:23:03<405:42:24,  2.75s/it]
  7%|▋         | 37550/569592 [6:23:08<492:36:09,  3.33s/it]
                                                            

  7%|▋         | 37550/569592 [6:23:08<492:36:09,  3.33s/it]
  7%|▋         | 37551/569592 [6:23:12<499:45:18,  3.38s/it]
                                                            

  7%|▋         | 37551/569592 [6:23:12<499:45:18,  3.38s/it]
  7%|▋         | 37552/569592 [6:23:15<490:28:14,  3.32s/it]
                                                            

  7%|▋         | 37552/569592 [6:23:15<490:28:14,  3.32s/it]
  7%|▋         | 37553/569592 [6:23:16<389:59:38,  2.64s/it]
                                                            

  7%|▋         | 37553/569592 [6:23:16<389:59:38,  2.64s/it]
  7%|▋         | 37554/569592 [6:23:17<314:16:35,  2.13s/it]
                                                            

  7%|▋         | 37554/569592 [6:23:17<314:16:35,  2.13s/it]
  7%|▋         | 37555/569592 [6:23:20<382:59:29,  2.59s/it]
                                                            

  7%|▋         | 37555/569592 [6:23:21<382:59:29,  2.59s/it]
  7%|▋         | 37556/569592 [6:23:21<310:35:35,  2.10s/it]
                                                            

  7%|▋         | 37556/569592 [6:23:21<310:35:35,  2.10s/it]
  7%|▋         | 37557/569592 [6:23:22<259:13:05,  1.75s/it]
                                                            

  7%|▋         | 37557/569592 [6:23:22<259:13:05,  1.75s/it]
  7%|▋         | 37558/569592 [6:23:26<341:47:26,  2.31s/it]
                                                            

  7%|▋         | 37558/569592 [6:23:26<341:47:26,  2.31s/it]
  7%|▋         | 37559/569592 [6:23:27<280:57:20,  1.90s/it]
                                                            

  7%|▋         | 37559/569592 [6:23:27<280:57:20,  1.90s/it]
  7%|▋         | 37560/569592 [6:23:28<237:42:22,  1.61s/it]
                                                            

  7%|▋         | 37560/569592 [6:23:28<237:42:22,  1.61s/it]
  7%|▋         | 37561/569592 [6:23:29<208:00:19,  1.41s/it]
                                                            

  7%|▋         | 37561/569592 [6:23:29<208:00/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (92370432 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
:19,  1.41s/it]
  7%|▋         | 37562/569592 [6:23:30<186:51:44,  1.26s/it]
                                                            

  7%|▋         | 37562/569592 [6:23:30<186:51:44,  1.26s/it]
  7%|▋         | 37563/569592 [6:23:32<218:44:44,  1.48s/it]
                                                            

  7%|▋         | 37563/569592 [6:23:32<218:44:44,  1.48s/it]
  7%|▋         | 37564/569592 [6:23:35<277:12:17,  1.88s/it]
                                                            

  7%|▋         | 37564/569592 [6:23:35<277:12:17,  1.88s/it]
  7%|▋         | 37565/569592 [6:23:39<388:02:18,  2.63s/it]
                                                            

  7%|▋         | 37565/569592 [6:23:39<388:02:18,  2.63s/it]
  7%|▋         | 37566/569592 [6:23:40<313:15:37,  2.12s/it]
                                                            

  7%|▋         | 37566/569592 [6:23:40<313:15:37,  2.12s/it]
  7%|▋         | 37567/569592 [6:23:42<323:36:28,  2.19s/it]
                                                            

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         /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                   

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                                                         /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
   

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  7%|▋         | 37768/569592 [6:33:26<43/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (93641436 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
6:12:06,  2.95s/it]
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  7%|▋         | 37773/569592 [6:33:39<378:14:35,  2.56s/it]
  7%|▋         | 37774/569592 [6:33:43<424:37:39,  2.87s/it]
                                                            

  7%|▋         | 37774/569592 [6:33:43<424:37:39,  2.87s/it]
  7%|▋         | 37775/569592 [6:33:44<339:34:42,  2.30s/it]
                                                            

  7%|▋         | 37775/569592 [6:33:44<339:34:42,  2.30s/it]
  7%|▋         | 37776/569592 [6:33:45<280:56:57,  1.90s/it]
                                                            

  7%|▋         | 37776/569592 [6:33:45<280:56:57,  1.90s/it]
  7%|▋         | 37777/569592 [6:33:49<369:14:58,  2.50s/it]
                                                            

  7%|▋         | 37777/569592 [6:33:49<369:14:58,  2.50s/it]
  7%|▋         | 37778/569592 [6:33:50<302:28:14,  2.05s/it]
                                                            

  7%|▋         | 37778/569592 [6:33:50<302:28:14,  2.05s/it]
  7%|▋         | 37779/569592 [6:33:53<367:35:16,  2.49s/it]
                                                            

  7%|▋         | 37779/569592 [6:33:53<367:35:16,  2.49s/it]
  7%|▋         | 37780/569592 [6:33:54<299:40:17,  2.03s/it]
                                                            

  7%|▋         | 37780/569592 [6:33:54<299:40:17,  2.03s/it]
  7%|▋         | 37781/569592 [6:33:58<373:02:02,  2.53s/it]
                                                            

  7%|▋         | 37781/569592 [6:33:58<373:02:02,  2.53s/it]
  7%|▋         | 37782/569592 [6:33:59<304:30:23,  2.06s/it]
                                                            

  7%|▋         | 37782/569592 [6:33:59<304:30:23,  2.06s/it]
  7%|▋         | 37783/569592 [6:34:03<375:56:28,  2.54s/it]
                                                            

  7%|▋         | 37783/569592 [6:34:03<375:56:28,  2.54s/it]
  7%|▋         | 37784/569592 [6:34:06<424:21:39,  2.87s/it]
                                                            

  7%|▋         | 37784/569592 [6:34:06<424:21:39,  2.87s/it]
  7%|▋         | 37785/569592 [6:34:07<343:08:40,  2.32s/it]
                                                            

  7%|▋         | 37785/569592 [6:34:07<343:08:40,  2.32s/it]
  7%|▋         | 37786/569592 [6:34:08<280:51:36,  1.90s/it]
                                                            

  7%|▋         | 37786/569592 [6:34:08<280:51:36,  1.90s/it]
  7%|▋         | 37787/569592 [6:34:09<237:58:21,  1.61s/it]
                                                            

  7%|▋         | 37787/569592 [6:34:09<237:58:21,  1.61s/it]
  7%|▋         | 37788/569592 [6:34:12<312:13:41,  2.11s/it]
                                                            

  7%|▋         | 37788/569592 [6:34:12<312:13:41,  2.11s/it]
  7%|▋         | 37789/569592 [6:34:16<373:48:50,  2.53s/it]
                                                            

  7%|▋         | 37789/569592 [6:34:16<373:48:50,  2.53s/it]
  7%|▋         | 37790/569592 [6:34:17<303:48:24,  2.06s/it]
                                                            

  7%|▋         | 37790/569592 [6:34:17<303:48:24,  2.06s/it]
  7%|▋         | 37791/569592 [6:34:20<361:16:13,  2.45s/it]
                                                            

  7%|▋         | 37791/569592 [6:34:20<361:16:13,  2.45s/it]
  7%|▋         | 37792/569592 [6:34:21<295:33:30,  2.00s/it]
                                                            

  7%|▋         | 37792/569592 [6:34:21<295:33:30,  2.00s/it]
  7%|▋         | 37793/569592 [6:34:25<372:57:31,  2.52s/it]
                                                            

  7%|▋         | 37793/569592 [6:34:25<372:57:31,  2.52s/it]
  7%|▋         | 37794/569592 [6:34:26<302:04:27,  2.04s/it]
                                                            

  7%|▋         | 37794/569592 [6:34:26<302:04:27,  2.04s/it]
  7%|▋         | 37795/569592 [6:34:30<408:16:26,  2.76s/it]
                                                            

  7%|▋         | 37795/569592 [6:34:30<408:16:26,  2.76s/it]
  7%|▋         | 37796/569592 [6:34:34<437:51:34,  2.96s/it]
                                                            

  7%|▋         | 37796/569592 [6:34:34<437:51:34,  2.96s/it]
  7%|▋         | 37797/569592 [6:34:35<354:33:25,  2.40s/it]
                                                            

  7%|▋         | 37797/569592 [6:34:35<354:33:25,  2.40s/it]
  7%|▋         | 37798/569592 [6:34:36<289:41:48,  1.96s/it]
                                                            

  7%|▋         | 37798/569592 [6:34:36<289:41:48,  1.96s/it]
  7%|▋         | 37799/569592 [6:34:41<423:56:42,  2.87s/it]
                                                            

  7%|▋         | 37799/569592 [6:34:41<423:56:42,  2.87s/it]
  7%|▋         | 37800/569592 [6:34:42<343:38:11,  2.33s/it]
                                                            

  7%|▋         | 37800/569592 [6:34:42<343:38:11,  2.33s/it]
  7%|▋         | 37801/569592 [6:34:43<281:32:42,  1.91s/it]
                                                            

  7%|▋         | 37801/569592 [6:34:43<281:32:42,  1.91s/it]
  7%|▋         | 37802/569592 [6:34:45<319:56:59,  2.17s/it]
                                                            

  7%|▋         | 37802/569592 [6:34:45<319:56:59,  2.17s/it]
  7%|▋         | 37803/569592 [6:34:50<428:22:45,  2.90s/it]
                                                            

  7%|▋         | 37803/569592 [6:34:50<428:22:45,  2.90s/it]
  7%|▋         | 37804/569592 [6:34:51<353:03:41,  2.39s/it]
                                                            

  7%|▋         | 37804/569592 [6:34:51<353:03:41,  2.39s/it]
  7%|▋         | 37805/569592 [6:34:52<289:18:21,  1.96s/it]
                                                            

  7%|▋         | 37805/569592 [6:34:52<289:18:21,  1.96s/it]
  7%|▋         | 37806/569592 [6:34:56<382:42:56,  2.59s/it]
                                                            

  7%|▋         | 37806/569592 [6:34:56<382:42:56,  2.59s/it]
  7%|▋         | 37807/569592 [6:35:01<484:54:58,  3.28s/it]
                                                            

  7%|▋         | 37807/569592 [6:35:01<484:54:58,  3.28s/it]
  7%|▋         | 37808/569592 [6:35:05<529:22:19,  3.58s/it]
                                                            

  7%|▋         | 37808/569592 [6:35:05<529:22:19,  3.58s/it]
  7%|▋         | 37809/569592 [6:35:09<523:03:21,  3.54s/it]
                                                            

  7%|▋         | 37809/569592 [6:35:09<523:03:21,  3.54s/it]
  7%|▋         | 37810/569592 [6:35:12<515:09:03,  3.49s/it]
                                                            

  7%|▋         | 37810/569592 [6:35:12<515:09:03,  3.49s/it]
  7%|▋         | 37811/569592 [6:35:16<505:48:46,  3.42s/it]
                                                            

  7%|▋         | 37811/569592 [6:35:16<505:48:46,  3.42s/it]
  7%|▋         | 37812/569592 [6:35:16<395:01:00,  2.67s/it]
                                                            

  7%|▋         | 37812/569592 [6:35:16<395:01:00,  2.67s/it]
  7%|▋         | 37813/569592 [6:35:20<446:28:34,  3.02s/it]
                                                            

  7%|▋         | 37813/569592 [6:35:20<446:28:34,  3.02s/it]
  7%|▋         | 37814/569592 [6:35:24<488:40:24,  3.31s/it]
                                                            

  7%|▋         | 37814/569592 [6:35:24<488:40:24,  3.31s/it]
  7%|▋         | 37815/569592 [6:35:28<490:37:09,  3.32s/it]
                                                            

  7%|▋         | 37815/569592 [6:35:28<490:37:09,  3.32s/it]
  7%|▋         | 37816/569592 [6:35:32<544:28:35,  3.69s/it]
                                                            

  7%|▋         | 37816/569592 [6:35:32<544:28:35,  3.69s/it]
  7%|▋         | 37817/569592 [6:35:33<420:16:40,  2.85s/it]
                                                            

  7%|▋         | 37817/569592 [6:35:33<420:16:40,  2.85s/it]
  7%|▋         | 37818/569592 [6:35:37<450:10:01,  3.05s/it]
                                                            

  7%|▋         | 37818/569592 [6:35:37<450:10:01,  3.05s/it]
  7%|▋         | 37819/569592 [6:35:40<480:58:40,  3.26s/it]
                                                            

  7%|▋         | 37819/569592 [6:35:40<480:58:40,  3.26s/it]
  7%|▋         | 37820/569592 [6:35:44<502:10:17,  3.40s/it]
                                                            

  7%|▋         | 37820/569592 [6:35:44<502:10:17,  3.40s/it]
  7%|▋         | 37821/569592 [6:35:47<491:46:46,  3.33s/it]
                                                            

  7%|▋         | 37821/569592 [6:35:47<491:46:46,  3.33s/it]
  7%|▋         | 37822/569592 [6:35:48<384:34:36,  2.60s/it]
                                                            

  7%|▋         | 37822/569592 [6:35:48<384:34:36,  2.60s/it]
  7%|▋         | 37823/569592 [6:35:52<433:10:10,  2.93s/it]
                                                            

  7%|▋         | 37823/569592 [6:35:52<433:10:10,  2.93s/it]
  7%|▋         | 37824/569592 [6:35:53<346:31:55,  2.35s/it]
                                                            

  7%|▋         | 37824/569592 [6:35:53<346:31:55,  2.35s/it]
  7%|▋         | 37825/569592 [6:35:54<285:58:15,  1.94s/it]
                                                            

  7%|▋         | 37825/569592 [6:35:54<285:58:15,  1.94s/it]
  7%|▋         | 37826/569592 [6:35:55<241:49:40,  1.64s/it]
                                                            

  7%|▋         | 37826/569592 [6:35:55<241:49:40,  1.64s/it]
  7%|▋         | 37827/569592 [6:35:56<209:41:15,  1.42s/it]
                                                            

  7%|▋         | 37827/569592 [6:35:56<209:41:15,  1.42s/it]
  7%|▋         | 37828/569592 [6:35:59<303:59:18,  2.06s/it]
                                                            

  7%|▋         | 37828/569592 [6:35:59<303:59:18,  2.06s/it]
  7%|▋         | 37829/569592 [6:36:03<373:17:55,  2.53s/it]
                                                            

  7%|▋         | 37829/569592 [6:36:03<373:17:55,  2.53s/it]
  7%|▋         | 37830/569592 [6:36:07<431:41:19,  2.92s/it]
                                                            

  7%|▋         | 37830/569592 [6:36:07<431:41:19,  2.92s/it]
  7%|▋         | 37831/569592 [6:36:10<465:31:05,  3.15s/it]
                                                            

  7%|▋         | 37831/569592 [6:36:10<465:31:05,  3.15s/it]
  7%|▋         | 37832/569592 [6:36:11<368:09:50,  2.49s/it]
                                                            

  7%|▋         | 37832/569592 [6:36:11<368:09:50,  2.49s/it]
  7%|▋         | 37833/569592 [6:36:12<299:38:09,  2.03s/it]
                                                            

  7%|▋         | 37833/569592 [6:36:12<299:38:09,  2.03s/it]
  7%|▋         | 37834/569592 [6:36:15<355:25:/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (92607408 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
15,  2.41s/it]
                                                            

  7%|▋         | 37834/569592 [6:36:16<355:25:15,  2.41s/it]
  7%|▋         | 37835/569592 [6:36:16<292:06:21,  1.98s/it]
                                                            

  7%|▋         | 37835/569592 [6:36:16<292:06:21,  1.98s/it]
  7%|▋         | 37836/569592 [6:36:20<347:51:24,  2.35s/it]
                                                            

  7%|▋         | 37836/569592 [6:36:20<347:51:24,  2.35s/it]
  7%|▋         | 37837/569592 [6:36:23<396:13:05,  2.68s/it]
                                                            

  7%|▋         | 37837/569592 [6:36:23<396:13:05,  2.68s/it]
  7%|▋         | 37838/569592 [6:36:27<457:09:24,  3.09s/it]
                                                            

  7%|▋         | 37838/569592 [6:36:27<457:09:24,  3.09s/it]
  7%|▋         | 37839/569592 [6:36:31<476:25:55,  3.23s/it]
                                                            

  7%|▋         | 37839/569592 [6:36:31<476:25:55,  3.23s/it]
  7%|▋         | 37840/569592 [6:36:36<562:01:44,  3.80s/it]
                                                            

  7%|▋         | 37840/569592 [6:36:36<562:01:44,  3.80s/it]
  7%|▋         | 37841/569592 [6:36:39<544:18:28,  3.69s/it]
                                                            

  7%|▋         | 37841/569592 [6:36:39<544:18:28,  3.69s/it]
  7%|▋         | 37842/569592 [6:36:42<522:15:55,  3.54s/it]
                                                            

  7%|▋         | 37842/569592 [6:36:43<522:15:55,  3.54s/it]
  7%|▋         | 37843/569592 [6:36:46<518:31:39,  3.51s/it]
                                                            

  7%|▋         | 37843/569592 [6:36:46<518:31:39,  3.51s/it]
  7%|▋         | 37844/569592 [6:36:49<503:18:21,  3.41s/it]
                                                            

  7%|▋         | 37844/569592 [6:36:49<503:18:21,  3.41s/it]
  7%|▋         | 37845/569592 [6:36:50<404:09:03,  2.74s/it]
                                                            

  7%|▋         | 37845/569592 [6:36:50<404:09:03,  2.74s/it]
  7%|▋         | 37846/569592 [6:36:51<325:58:04,  2.21s/it]
                                                            

  7%|▋         | 37846/569592 [6:36:51<325:58:04,  2.21s/it]
  7%|▋         | 37847/569592 [6:36:55<373:32:21,  2.53s/it]
                                                            

  7%|▋         | 37847/569592 [6:36:55<373:32:21,  2.53s/it]
  7%|▋         | 37848/569592 [6:36:58<410:19:04,  2.78s/it]
                                                            

  7%|▋         | 37848/569592 [6:36:58<410:19:04,  2.78s/it]
  7%|▋         | 37849/569592 [6:36:59<328:21:38,  2.22s/it]
                                                            

  7%|▋         | 37849/569592 [6:36:59<328:21:38,  2.22s/it]
  7%|▋         | 37850/569592 [6:37:03<396:47:49,  2.69s/it]
                                                            

  7%|▋         | 37850/569592 [6:37:03<396:47:49,  2.69s/it]
  7%|▋         | 37851/569592 [6:37:06<440:04:07,  2.98s/it]
                                                            

  7%|▋         | 37851/569592 [6:37:06<440:04:07,  2.98s/it]
  7%|▋         | 37852/569592 [6:37:10<457:38:56,  3.10s/it]
                                                            

  7%|▋         | 37852/569592 [6:37:10<457:38:56,  3.10s/it]
  7%|▋         | 37853/569592 [6:37:13<488:44:31,  3.31s/it]
                                                            

  7%|▋         | 37853/569592 [6:37:13<488:44:31,  3.31s/it]
  7%|▋         | 37854/569592 [6:37:17<486:04:36,  3.29s/it]
                                                            

  7%|▋         | 37854/569592 [6:37:17<486:04:36,  3.29s/it]
  7%|▋         | 37855/569592 [6:37:20<487:22:57,  3.30s/it]
                                                            

  7%|▋         | 37855/569592 [6:37:20<487:22:57,  3.30s/it]
  7%|▋         | 37856/569592 [6:37:23<488:35:42,  3.31s/it]
                                                            

  7%|▋         | 37856/569592 [6:37:23<488:35:42,  3.31s/it]
  7%|▋         | 37857/569592 [6:37:28<536:18:33,  3.63s/it]
                                                            

  7%|▋         | 37857/569592 [6:37:28<536:18:33,  3.63s/it]
  7%|▋         | 37858/569592 [6:37:31<511:45:01,  3.46s/it]
                                                            

  7%|▋         | 37858/569592 [6:37:31<511:45:01,  3.46s/it]
  7%|▋         | 37859/569592 [6:37:35<527:59:58,  3.57s/it]
                                                            

  7%|▋         | 37859/569592 [6:37:35<527:59:58,  3.57s/it]
  7%|▋         | 37860/569592 [6:37:38<523:11:16,  3.54s/it]
                                                            

  7%|▋         | 37860/569592 [6:37:38<523:11:16,  3.54s/it]
  7%|▋         | 37861/569592 [6:37:41<513:50:59,  3.48s/it]
                                                            

  7%|▋         | 37861/569592 [6:37:41<513:50:59,  3.48s/it]
  7%|▋         | 37862/569592 [6:37:45<507:03:44,  3.43s/it]
                                                            

  7%|▋         | 37862/569592 [6:37:45<507:03:44,  3.43s/it]
  7%|▋         | 37863/569592 [6:37:48<503:56:57,  3.41s/it]
                                                            

  7%|▋         | 37863/569592 [6:37:48<503:56:57,  3.41s/it]
  7%|▋         | 37864/569592 [6:37:51<486:50:23,  3.30s/it]
                                                            

  7%|▋         | 37864/569592 [6:37:51<486:50:23,  3.30s/it]
  7%|▋         | 37865/569592 [6:37:54<489:55:45,  3.32s/it]
                                                            

  7%|▋         | 37865/569592 [6:37:55<489:55:45,  3.32s/it]
  7%|▋         | 37866/569592 [6:37:58<488:13:01,  3.31s/it]
                                                            

  7%|▋         | 37866/569592 [6:37:58<488:13:01,  3.31s/it]
  7%|▋         | 37867/569592 [6:38:01<482:59:57,  3.27s/it]
                                                            

  7%|▋         | 37867/569592 [6:38:01<482:59:57,  3.27s/it]
  7%|▋         | 37868/569592 [6:38:05<495:58:36,  3.36s/it]
                                                            

  7%|▋         | 37868/569592 [6:38:05<495:58:36,  3.36s/it]
  7%|▋         | 37869/569592 [6:38:08<507:38:34,  3.44s/it]
                                                            

  7%|▋         | 37869/569592 [6:38:08<507:38:34,  3.44s/it]
  7%|▋         | 37870/569592 [6:38:12<514:16:56,  3.48s/it]
                                                            

  7%|▋         | 37870/569592 [6:38:12<514:16:56,  3.48s/it]
  7%|▋         | 37871/569592 [6:38:15<503:00:14,  3.41s/it]
                                                            

  7%|▋         | 37871/569592 [6:38:15<503:00:14,  3.41s/it]
  7%|▋         | 37872/569592 [6:38:19<550:32:33,  3.73s/it]
                                                            

  7%|▋         | 37872/569592 [6:38:19<550:32:33,  3.73s/it]
  7%|▋         | 37873/569592 [6:38:23<539:06:44,  3.65s/it]
                                                            

  7%|▋         | 37873/569592 [6:38:23<539:06:44,  3.65s/it]
  7%|▋         | 37874/569592 [6:38:26<507:45:24,  3.44s/it]
                                                            

  7%|▋         | 37874/569592 [6:38:26<507:45:24,  3.44s/it]
  7%|▋         | 37875/569592 [6:38:29<507:50:47,  3.44s/it]
                                                            

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  7%|▋         | 37877/569592/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 [6:38:37<515:21:10,  3.49s/it]
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  7%|▋         | 37894/569592 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
[6:39:17<262:27:08,  1.78s/it]
                                                            

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                                                         /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (96000000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
   

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  7%|▋         | 37964/569592 [6:42:22<481:40:35,  3.26s//home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
it]
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  7%|▋         | 38000/569592 [6:44:25<467:12:26,  3.16s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-38000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-38000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-38000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-38000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-38000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-38000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-37000] due to args.save_total_limit

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  warnings.warn(
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  warnings.warn(
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  7%|▋         | 38109/569592/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 [6:51:39<326:55:21,  2.21s/it]
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                                                     /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (116985253 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
       

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                                                         /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (101756928 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
   

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                     /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (91364286 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                       

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 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                           

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                                             /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (93641436 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
               

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  7%|▋         | 38411/569592 [7:05:37<413:53:10,  2.81s/it]
                                                            

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  7%|▋         | 38413/569592 [7:05:45<501:46:32,  3.40s/it]
                                                            

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  7%|▋         | 38416/569592 [7:05:52<382:36:20,  2.59s/it]
                                                            

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  7%|▋         | 38421/569592 [7:06:02<265:43:54,  1.80s/it]
                                                            

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  7%|▋         | /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
38474/569592 [7:08:43<352:25:41,  2.39s/it]
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  7%|▋         | 3852/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
3/569592 [7:10:49<435:02:26,  2.95s/it]
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                             /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (92980130 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                               

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             /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                               

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/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (104994628 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

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  7%|▋         | 38802/569592 [7:24:01<483:01:45,  3.28s/it]
                                                            

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  7%|▋         | 38803/569592 [7:24:05<496:44:38,  3.37s/it]
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  7%|▋         | 38807/569592 [7:24:16<399:48:10,  2.71s/it]
  7%|▋         | 38808/569592 [7:24:20<435:37:14,  2.95s/it]
                                                            

  7%|▋         | 38808/569592 [7:24:20<435:37:14,  2.95s/it]
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  7%|▋         | 38809/569592 [7:24:24<499:00:41,  3.38s/it]
  7%|▋         | 38810/569592 [7:24:28<501:29:57,  3.40s/it]
                                                            

  7%|▋         | 38810/569592 [7:24:28<501:29:57,  3.40s/it]
  7%|▋         | 38811/569592 [7:24:29<391:05:06,  2.65s/it]
                                                            

  7%|▋         | 38811/569592 [7:24:29<391:05:06,  2.65s/it]
  7%|▋         | 38812/569592 [7:24:32<425:58:33,  2.89s/it]
                                                            

  7%|▋         | 38812/569592 [7:24:32<425:58:33,  2.89s/it]
  7%|▋         | 38813/569592 [7:24:36<460:15:01,  3.12s/it]
                                                            

  7%|▋         | 38813/569592 [7:24:36<460:15:01,  3.12s/it]
  7%|▋         | 38814/569592 [7:24:39<474:53:27,  3.22s/it]
                                                            

  7%|▋         | 38814/569592 [7:24:39<474:53:27,  3.22s/it]
  7%|▋         | 38815/569592 [7:24:40<374:41:47,  2.54s/it]
                                                            

  7%|▋         | 38815/569592 [7:24:40<374:41:47,  2.54s/it]
  7%|▋         | 38816/569592 [7:24:41<303:06:53,  2.06s/it]
                                                            

  7%|▋         | 38816/569592 [7:24:41<303:06:53,  2.06s/it]
  7%|▋         | 38817/569592 [7:24:42<255:50:39,  1.74s/it]
                                                            

  7%|▋         | 38817/569592 [7:24:42<255:50/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (103483016 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
:39,  1.74s/it]
  7%|▋         | 38818/569592 [7:24:43<221:46:20,  1.50s/it]
                                                            

  7%|▋         | 38818/569592 [7:24:43<221:46:20,  1.50s/it]
  7%|▋         | 38819/569592 [7:24:48<376:07:31,  2.55s/it]
                                                            

  7%|▋         | 38819/569592 [7:24:48<376:07:31,  2.55s/it]
  7%|▋         | 38820/569592 [7:24:51<410:28:19,  2.78s/it]
                                                            

  7%|▋         | 38820/569592 [7:24:51<410:28:19,  2.78s/it]
  7%|▋         | 38821/569592 [7:24:52<330:58:32,  2.24s/it]
                                                            

  7%|▋         | 38821/569592 [7:24:52<330:58:32,  2.24s/it]
  7%|▋         | 38822/569592 [7:24:56<395:47:04,  2.68s/it]
                                                            

  7%|▋         | 38822/569592 [7:24:56<395:47:04,  2.68s/it]
  7%|▋         | 38823/569592 [7:24:57<323:08:28,  2.19s/it]
                                                            

  7%|▋         | 38823/569592 [7:24:57<323:08:28,  2.19s/it]
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  7%|▋         | 38832/569592 [7:25:17<305:37:23,  2.07s/it]
                                                            

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  7%|▋         | 38833/569592 [7:25:21<400:22:23,  2.72s/it]
                                                            

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  7%|▋         | 38851/569592 [7:26:06<361:35:57,  2.45s/it]
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  7%|▋         | 38860/569592 [7:26:30<419:12:31,  2.84s/it]
  7%|▋         | 38861/569592 [7:26:31<337:05:44,  2.29s/it]
                                                            

  7%|▋         | 38861/569592 [7:26:31<337:05:44,  2.29s/it]
  7%|▋         | 38862/569592 [7:26:35<396:39:54,  2.69s/it]
                                                            

  7%|▋         | 38862/569592 [7:26:35<396:39:54,  2.69s/it]
  7%|▋         | 38863/569592 [7:26:39<447:35:50,  3.04s/it]
                                                            

  7%|▋         | 38863/569592 [7:26:39<447:35:50,  3.04s/it]
  7%|▋         | 38864/569592 [7:26:40<355:47:42,  2.41s/it]
                                                            

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  7%|▋         | 38866/569592 [7:26:45<369:34:26,  2.51s/it]
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  7%|▋         | 38867/569592 [7:26:48<427:23:37,  2.90s/it]
  7%|▋         | 38868/569592 [7:26:52<460:21:41,  3.12s/it]
                                                            

  7%|▋         | 38868/569592 [7:26:52<460:21:41,  3.12s/it]
  7%|▋         | 38869/569592 [7:26:55<470:35:21,  3.19s/it]
                                                            

  7%|▋         | 38869/569592 [7:26:55<470:35:21,  3.19s/it]
  7%|▋         | 38870/569592 [7:26:59<480:23:16,  3.26s/it]
                                                            

  7%|▋         | 38870/569592 [7:26:59<480:23:16,  3.26s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

  7%|▋         | 38871/569592 [7:27:00<376:01:14,  2.55s/it]
                                                            

  7%|▋         | 38871/569592 [7:27:00<376:01:14,  2.55s/it]
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  7%|▋         | 38876/569592 [7:27:16<469:11:30,  3.18s/it]
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  7%|▋         | 38879/569592 [7:27:23<414:10:45,  2.81s/it]
                                                            

  7%|▋         | 38879/569592 [7:27:23<414:10:45,  2.81s/it]
  7%|▋         | 38880/569592 [7:27:26<427:59:09,  2.90s/it]
                                                            

  7%|▋         | 38880/569592 [7:27:26<427:59:09,  2.90s/it]
  7%|▋         | 38881/569592 [7:27:30<442:16:54,  3.00s/it]
                                                            

  7%|▋         | 38881/569592 [7:27:30<442:16:54,  3.00s/it]
  7%|▋         | 38882/569592 [7:27:31<350:16:21,  2.38s/it]
                                                            

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  7%|▋         | 38884/569592 [7:27:35<356:41:39,  2.42s/it]
                                                            

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  7%|▋         | 38890/569592 [7:27:54<440:52:03,  2.99s/it]
  7%|▋         | 38891/569592 [7:27:57<465:06:49,  3.16s/it]
                                                            

  7%|▋         | 38891/569592 [7:27:57<465:06:49,  3.16s/it]
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  7%|▋         | 38892/569592 [7:28:01<487:42:39,  3.31s/it]
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  7%|▋         | 38904/569592 [7:28:42<517:19:42,  3.51s/it]
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  7%|▋         | 38905/569592 [7:28:45<499:55:18,  3.39s/it]
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  7%|▋         | 38985/569592 [7:32:22<262:22:15,  1.78s/it]
        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                    

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  7%|▋         | 39000/569592 [7:33:07<503:10:22,  3.41s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-39000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-39000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-39000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-39000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-39000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-39000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-38000] due to args.save_total_limit

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    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                         

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  7%|▋ /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
        | 39137/569592 [7:41:51<481:52:27,  3.27s/it]
                                                            

  7%|▋         | 39137/569592 [7:41:51<481:52:27,  3.27s/it]
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  7%|▋         | 39147/569592 [7:42:23<480:59:54, /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (101756928 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 3.26s/it]
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  7%|▋         | 39253/569592 [7:47:11<292:25:50,  1.99s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (99599360 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

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  7%|▋         | 3929/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
2/569592 [7:49:01<313:34:31,  2.13s/it]
                                                            

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    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100225125 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                        

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  7%|▋         | 39380/569592 [7:53:16<519:44:24,  3.53s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

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/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (94547712 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                            

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  7%|�/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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                            /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                

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  7%|▋  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95054278 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
       | 39511/569592 [7:59:23<392:08:35,  2.66s/it]
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  7%|▋         | 39517/569592/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (91449844 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 [7:59:42<449:04:22,  3.05s/it]
                                                            

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                                /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98214944 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                            

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  warnings.warn(
12s/it]
                                                            

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  7%|▋         | 3967/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (92503620 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
5/569592 [8:06:50<464:40:07,  3.16s/it]
                                                            

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  7%|�/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (93548736 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  7%|▋         | 39734/569592 [8:09:40<348:24:31,  2.37s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (93571090 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

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                                            /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                

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  7/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100663296 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  7%|▋   /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (93657560 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
      | 39882/569592 [8:16:41<239:32:57,  1.63s/it]
                                                            

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  warnings.warn(
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  warnings.warn(

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  7%|▋         | 40000/569592 [8:22:17<220:18:34,  1.50s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-40000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-40000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-40000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-40000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-40000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-40000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-39000] due to args.save_total_limit


model-00001-of-00006.safetensors:   0%|          | 0.00/4.97G [00:00<?, ?B/s]


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            /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                

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  warnings.warn(
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  7%|▋         | 40072/569592 [8:30:18<393:08:39,  2.67s/it]
  7%|▋         | 40073/569592 [8:30:23<469:26:58,  3.19s/it]
                                                            

  7%|▋         | 40073/569592 [8:30:23<469:26:58,  3.19s/it]
  7%|▋         | 40074/569592 [8:30:27<541:42:33,  3.68s/it]
                                                            

  7%|▋         | 40074/569592 [8:30:27<541:42:33,  3.68s/it]
  7%|▋         | 40075/569592 [8:30:28<417:21:07,  2.84s/it]
                                                            

  7%|▋         | 40075/569592 [8:30:28<417:21:07,  2.84s/it]
  7%|▋         | 40076/569592 [8:30:32<454:37:18,  3.09s/it]
                                                            

  7%|▋         | 40076/569592 [8:30:32<454:37:18,  3.09s/it]
  7%|▋         | 40077/569592 [8:30:36<503:11:21,  3.42s/it]
                                                            

  7%|▋         | 40077/569592 [8:30:36<503:11:21,  3.42s/it]
  7%|▋         | 40078/569592 [8:30:39<496:41:06,  3.38s/it]
                                                            

  7%|▋         | 40078/569592 [8:30:39<496:41:06,  3.38s/it]
  7%|▋         | 40079/569592 [8:30:43<496:35:57,  3.38s/it]
                                                            

  7%|▋         | 40079/569592 [8:30:43<496:35:57,  3.38s/it]
  7%|▋         | 40080/569592 [8:30:47<517:40:16,  3.52s/it]
                                                            

  7%|▋         | 40080/569592 [8:30:47<517:40:16,  3.52s/it]
  7%|▋         | 40081/569592 [8:30:50<521:10:05,  3.54s/it]
                                                            

  7%|▋         | 40081/569592 [8:30:50<521:10:05,  3.54s/it]
  7%|▋         | 40082/569592 [8:30:51<405:34:25,  2.76s/it]
                                    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100476176 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                        

  7%|▋         | 40082/569592 [8:30:51<405:34:25,  2.76s/it]
  7%|▋         | 40083/569592 [8:30:52<325:35:33,  2.21s/it]
                                                            

  7%|▋         | 40083/569592 [8:30:52<325:35:33,  2.21s/it]
  7%|▋         | 40084/569592 [8:30:56<413:31:13,  2.81s/it]
                                                            

  7%|▋         | 40084/569592 [8:30:56<413:31:13,  2.81s/it]
  7%|▋         | 40085/569592 [8:30:57<331:10:55,  2.25s/it]
                                                            

  7%|▋         | 40085/569592 [8:30:57<331:10:55,  2.25s/it]
  7%|▋         | 40086/569592 [8:31:01<393:58:03,  2.68s/it]
                                                            

  7%|▋         | 40086/569592 [8:31:01<393:58:03,  2.68s/it]
  7%|▋         | 40087/569592 [8:31:05<471:13:28,  3.20s/it]
                                                            

  7%|▋         | 40087/569592 [8:31:05<471:13:28,  3.20s/it]
  7%|▋         | 40088/569592 [8:31:10<537:38:04,  3.66s/it]
                                                            

  7%|▋         | 40088/569592 [8:31:10<537:38:04,  3.66s/it]
  7%|▋         | 40089/569592 [8:31:13<523:04:11,  3.56s/it]
                                                            

  7%|▋         | 40089/569592 [8:31:13<523:04:11,  3.56s/it]
  7%|▋         | 40090/569592 [8:31:17<504:26:46,  3.43s/it]
                                                            

  7%|▋         | 40090/569592 [8:31:17<504:26:46,  3.43s/it]
  7%|▋         | 40091/569592 [8:31:20<496:07:07,  3.37s/it]
                                                            

  7%|▋         | 40091/569592 [8:31:20<496:07:07,  3.37s/it]
  7%|▋         | 40092/569592 [8:31:21<387:30:34,  2.63s/it]
                                                            

  7%|▋         | 40092/569592 [8:31:21<387:30:34,  2.63s/it]
  7%|▋         | 40093/569592 [8:31:25<478:51:44,  3.26s/it]
                                                            

  7%|▋         | 40093/569592 [8:31:25<478:51:44,  3.26s/it]
  7%|▋         | 40094/569592 [8:31:29<494:21:59,  3.36s/it]
                                                            

  7%|▋         | 40094/569592 [8:31:29<494:21:59,  3.36s/it]
  7%|▋         | 40095/569592 [8:31:33<508:03:58,  3.45s/it]
                                                            

  7%|▋         | 40095/569592 [8:31:33<508:03:58,  3.45s/it]
  7%|▋         | 40096/569592 [8:31:36<505:47:53,  3.44s/it]
                                                            

  7%|▋         | 40096/569592 [8:31:36<505:47:53,  3.44s/it]
  7%|▋         | 40097/569592 [8:31:37<393:41:23,  2.68s/it]
                                                            

  7%|▋         | 40097/569592 [8:31:37<393:41:23,  2.68s/it]
  7%|▋         | 40098/569592 [8:31:38<316:04:00,  2.15s/it]
                                                            

  7%|▋         | 40098/569592 [8:31:38<316:04:00,  2.15s/it]
  7%|▋         | 40099/569592 [8:31:39<270:27:21,  1.84s/it]
                                                            

  7%|▋         | 40099/569592 [8:31:39<270:27:21,  1.84s/it]
  7%|▋         | 40100/569592 [8:31:44<420:56:43,  2.86s/it]
                                                            

  7%|▋         | 40100/569592 [8:31:44<420:56:43,  2.86s/it]
  7%|▋         | 40101/569592 [8:31:49<517:04:37,  3.52s/it]
                                                            

  7%|▋         | 40101/569592 [8:31:49<517:04:37,  3.52s/it]
  7%|▋         | 40102/569592 [8:31:50<401:42:14,  2.73s/it]
                                                            

  7%|▋         | 40102/569592 [8:31:50<401:42:14,  2.73s/it]
  7%|▋         | 40103/569592 [8:31:51<325:29:10,  2.21s/it]
                                                            

  7%|▋         | 40103/569592 [8:31:51<325:29:10,  2.21s/it]
  7%|▋         | 40104/569592 [8:31:55<407:06:27,  2.77s/it]
                                                            

  7%|▋         | 40104/569592 [8:31:55<407:06:27,  2.77s/it]
  7%|▋         | 40105/569592 [8:31:56<327:30:26,  2.23s/it]
                                                            

  7%|▋         | 40105/569592 [8:31:56<327:30:26,  2.23s/it]
  7%|▋         | 40106/569592 [8:31:57<270:39:15,  1.84s/it]
                                                            

  7%|▋         | 40106/569592 [8:31:57<270:39:15,  1.84s/it]
  7%|▋         | 40107/569592 [8:31:58<233:05:55,  1.58s/it]
                                                            

  7%|▋         | 40107/569592 [8:31:58<233:05:55,  1.58s/it]
  7%|▋         | 40108/569592 [8:31:59<204:11:38,  1.39s/it]
                                                            

  7%|▋         | 40108/569592 [8:31:59<204:11:38,  1.39s/it]
  7%|▋         | 40109/569592 [8:32:04<370:45:08,  2.52s/it]
                                                            

  7%|▋         | 40109/569592 [8:32:04<370:45:08,  2.52s/it]
  7%|▋         | 40110/569592 [8:32:09<448:58:32,  3.05s/it]
                                                            

  7%|▋         | 40110/569592 [8:32:09<448:58:32,  3.05s/it]
  7%|▋         | 40111/569592 [8:32:12<454:09:29,  3.09s/it]
                                                            

  7%|▋         | 40111/569592 [8:32:12<454:09:29,  3.09s/it]
  7%|▋         | 40112/569592 [8:32:13<362:07:40,  2.46s/it]
                                                            

  7%|▋         | 40112/569592 [8:32:13<362:07:40,  2.46s/it]
  7%|▋         | 40113/569592 [8:32:14<294:49:14,  2.00s/it]
                                                            

  7%|▋         | 40113/569592 [8:32:14<294:49:14,  2.00s/it]
  7%|▋         | 40114/569592 [8:32:15<248:10:33,  1.69s/it]
                                                            

  7%|▋         | 40114/569592 [8:32:15<248:10:33,  1.69s/it]
  7%|▋         | 40115/569592 [8:32:16<214:34:57,  1.46s/it]
                                                            

  7%|▋         | 40115/569592 [8:32:16<214:34:57,  1.46s/it]
  7%|▋         | 40116/569592 [8:32:17<214:07:19,  1.46s/it]
                                                            

  7%|▋         | 40116/569592 [8:32:17<214:07:19,  1.46s/it]
  7%|▋         | 40117/569592 [8:32:21<306:07:44,  2.08s/it]
                                                            

  7%|▋         | 40117/569592 [8:32:21<306:07:44,  2.08s/it]
  7%|▋         | 40118/569592 [8:32:24<359:45:46,  2.45s/it]
                                                            

  7%|▋         | 40118/569592 [8:32:24<359:45:46,  2.45s/it]
  7%|▋         | 40119/569592 [8:32:28<421:25:47,  2.87s/it]
                                                            

  7%|▋         | 40119/569592 [8:32:28<421:25:47,  2.87s/it]
  7%|▋         | 40120/569592 [8:32:32<481:34:16,  3.27s/it]
                                                            

  7%|▋         | 40120/569592 [8:32:32<481:34:16,  3.27s/it]
  7%|▋         | 40121/569592 [8:32:33<381:04:18,  2.59s/it]
                                                            

  7%|▋         | 40121/569592 [8:32:33<381:04:18,  2.59s/it]
  7%|▋         | 40122/569592 [8:32:36<419:16:39,  2.85s/it]
                                                            

  7%|▋         | 40122/569592 [8:32:36<419:16:39,  2.85s/it]
  7%|▋         | 40123/569592 [8:32:40<465:27:38,  3.16s/it]
                                                            

  7%|▋         | 40123/569592 [8:32:40<465:27:38,  3.16s/it]
  7%|▋         | 40124/569592 [8:32:41<368:19:46,  2.50s/it]
                                                            

  7%|▋         | 40124/569592 [8:32:41<368:19:46,  2.50s/it]
  7%|▋         | 40125/569592 [8:32:45<435:54:12,  2.96s/it]
                                                            

  7%|▋         | 40125/569592 [8:32:45<435:54:12,  2.96s/it]
  7%|▋         | 40126/569592 [8:32:49<475:27:35,  3.23s/it]
                                                            

  7%|▋         | 40126/569592 [8:32:49<475:27:35,  3.23s/it]
  7%|▋         | 40127/569592 [8:32:54<525:27:56,  3.57s/it]
                                                            

  7%|▋         | 40127/569592 [8:32:54<525:27:56,  3.57s/it]
  7%|▋         | 40128/569592 [8:32:54<408:16:36,  2.78s/it]
                                                            

  7%|▋         | 40128/569592 [8:32:54<408:16:36,  2.78s/it]
  7%|▋         | 40129/569592 [8:32:58<425:44:46,  2.89s/it]
                                                            

  7%|▋         | 40129/569592 [8:32:58<425:44:46,  2.89s/it]
  7%|▋         | 40130/569592 [8:32:59<339:12:41,  2.31s/it]
                                                            

  7%|▋         | 40130/569592 [8:32:59<339:12:41,  2.31s/it]
  7%|▋         | 40131/569592 [8:32:59<279:23:11,  1.90s/it]
                                                            

  7%|▋         | 40131/569592 [8:33:00<279:23:11,  1.90s/it]
  7%|▋         | 40132/569592 [8:33:00<238:49:11,  1.62s/it]
                                                            

  7%|▋         | 40132/569592 [8:33:00<238:49:11,  1.62s/it]
  7%|▋         | 40133/569592 [8:33:02<213:48:59,  1.45s/it]
                                                            

  7%|▋         | 40133/569592 [8:33:02<213:48:59,  1.45s/it]
  7%|▋         | 40134/569592 [8:33:05<298:36:57,  2.03s/it]
                                                            

  7%|▋         | 40134/569592 [8:33:05<298:36:57,  2.03s/it]
  7%|▋         | 40135/569592 [8:33:12<508:15:14,  3.46s/it]
                                                            

  7%|▋         | 40135/569592 [8:33:12<508:15:14,  3.46s/it]
  7%|▋         | 40136/569592 [8:33:16<529:12:02,  3.60s/it]
                                                            

  7%|▋         | 40136/569592 [8:33:16<529:12:02,  3.60s/it]
  7%|▋         | 40137/569592 [8:33:19<516:59:38,  3.52s/it]
                                                            

  7%|▋         | 40137/569592 [8:33:19<516:59:38,  3.52s/it]
  7%|▋         | 40138/569592 [8:33:22<508:43:07,  3.46s/it]
                                                            

  7%|▋         | 40138/569592 [8:33:22<508:43:07,  3.46s/it]
  7%|▋         | 40139/569592 [8:33:23<399:08:11,  2.71s/it]
                                                            

  7%|▋         | 40139/569592 [8:33:23<399:08:11,  2.71s/it]
  7%|▋         | 40140/569592 [8:33:24<321:23:55,  2.19s/it]
                                                            

  7%|▋         | 40140/569592 [8:33:24<321:23:55,  2.19s/it]
  7%|▋         | 40141/569592 [8:33:25<266:23:17,  1.81s/it]
                                                            

  7%|▋         | 40141/569592 [8:33:25<266:23:17,  1.81s/it]
  7%|▋         | 40142/569592 [8:33:30<384:29:40,  2.61s/it]
                    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                        

  7%|▋         | 40142/569592 [8:33:30<384:29:40,  2.61s/it]
  7%|▋         | 40143/569592 [8:33:34<443:57:00,  3.02s/it]
                                                            

  7%|▋         | 40143/569592 [8:33:34<443:57:00,  3.02s/it]
  7%|▋         | 40144/569592 [8:33:35<351:45:10,  2.39s/it]
                                                            

  7%|▋         | 40144/569592 [8:33:35<351:45:10,  2.39s/it]
  7%|▋         | 40145/569592 [8:33:35<287:50:36,  1.96s/it]
                                                            

  7%|▋         | 40145/569592 [8:33:35<287:50:36,  1.96s/it]
  7%|▋         | 40146/569592 [8:33:39<353:49:36,  2.41s/it]
                                                            

  7%|▋         | 40146/569592 [8:33:39<353:49:36,  2.41s/it]
  7%|▋         | 40147/569592 [8:33:43<406:08:46,  2.76s/it]
                                                            

  7%|▋         | 40147/569592 [8:33:43<406:08:46,  2.76s/it]
  7%|▋         | 40148/569592 [8:33:43<327:23:44,  2.23s/it]
                                                            

  7%|▋         | 40148/569592 [8:33:43<327:23:44,  2.23s/it]
  7%|▋         | 40149/569592 [8:33:48<414:04:11,  2.82s/it]
                                                            

  7%|▋         | 40149/569592 [8:33:48<414:04:11,  2.82s/it]
  7%|▋         | 40150/569592 [8:33:49<334:05:47,  2.27s/it]
                                                            

  7%|▋         | 40150/569592 [8:33:49<334:05:47,  2.27s/it]
  7%|▋         | 40151/569592 [8:33:52<401:06:51,  2.73s/it]
                                                            

  7%|▋         | 40151/569592 [8:33:52<401:06:51,  2.73s/it]
  7%|▋         | 40152/569592 [8:33:56<435:16:26,  2.96s/it]
                                                            

  7%|▋         | 40152/569592 [8:33:56<435:16:26,  2.96s/it]
  7%|▋         | 40153/569592 [8:33:59<454:51:35,  3.09s/it]
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (97470000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                            

  7%|▋         | 40153/569592 [8:33:59<454:51:35,  3.09s/it]
  7%|▋         | 40154/569592 [8:34:03<473:07:39,  3.22s/it]
                                                            

  7%|▋         | 40154/569592 [8:34:03<473:07:39,  3.22s/it]
  7%|▋         | 40155/569592 [8:34:06<478:14:54,  3.25s/it]
                                                            

  7%|▋         | 40155/569592 [8:34:06<478:14:54,  3.25s/it]
  7%|▋         | 40156/569592 [8:34:10<483:43:18,  3.29s/it]
                                                            

  7%|▋         | 40156/569592 [8:34:10<483:43:18,  3.29s/it]
  7%|▋         | 40157/569592 [8:34:10<378:28:54,  2.57s/it]
                                                            

  7%|▋         | 40157/569592 [8:34:11<378:28:54,  2.57s/it]
  7%|▋         | 40158/569592 [8:34:11<307:30:46,  2.09s/it]
                                                            

  7%|▋         | 40158/569592 [8:34:11<307:30:46,  2.09s/it]
  7%|▋         | 40159/569592 [8:34:15<366:20:25,  2.49s/it]
                                                            

  7%|▋         | 40159/569592 [8:34:15<366:20:25,  2.49s/it]
  7%|▋         | 40160/569592 [8:34:19<435:05:40,  2.96s/it]
                                                            

  7%|▋         | 40160/569592 [8:34:19<435:05:40,  2.96s/it]
  7%|▋         | 40161/569592 [8:34:23<471:04:17,  3.20s/it]
                                                            

  7%|▋         | 40161/569592 [8:34:23<471:04:17,  3.20s/it]
  7%|▋         | 40162/569592 [8:34:24<369:13:36,  2.51s/it]
                                                            

  7%|▋         | 40162/569592 [8:34:24<369:13:36,  2.51s/it]
  7%|▋         | 40163/569592 [8:34:28<433:05:41,  2.94s/it]
                                                            

  7%|▋         | 40163/569592 [8:34:28<433:05:41,  2.94s/it]
  7%|▋         | 40164/569592 [8:34:31<476:08:24,  3.24s/it]
                                                            

  7%|▋         | 40164/569592 [8:34:31<476:08:24,  3.24s/it]
  7%|▋         | 40165/569592 [8:34:35<479:26:12,  3.26s/it]
                                                            

  7%|▋         | 40165/569592 [8:34:35<479:26:12,  3.26s/it]
  7%|▋         | 40166/569592 [8:34:38<479:08:06,  3.26s/it]
                                                            

  7%|▋         | 40166/569592 [8:34:38<479:08:06,  3.26s/it]
  7%|▋         | 40167/569592 [8:34:43<537:35:47,  3.66s/it]
                                                            

  7%|▋         | 40167/569592 [8:34:43<537:35:47,  3.66s/it]
  7%|▋         | 40168/569592 [8:34:46<505:05:29,  3.43s/it]
                                                            

  7%|▋         | 40168/569592 [8:34:46<505:05:29,  3.43s/it]
  7%|▋         | 40169/569592 [8:34:49<524:07:37,  3.56s/it]
                                                            

  7%|▋         | 40169/569592 [8:34:49<524:07:37,  3.56s/it]
  7%|▋         | 40170/569592 [8:34:53<533:37:57,  3.63s/it]
                                                            

  7%|▋         | 40170/569592 [8:34:53<533:37:57,  3.63s/it]
  7%|▋         | 40171/569592 [8:34:57<539:17:09,  3.67s/it]
                                                            

  7%|▋         | 40171/569592 [8:34:57<539:17:09,  3.67s/it]
  7%|▋         | 40172/569592 [8:35:01<539:45:42,  3.67s/it]
                                                            

  7%|▋         | 40172/569592 [8:35:01<539:45:42,  3.67s/it]
  7%|▋         | 40173/569592 [8:35:04<548:06:41,  3.73s/it]
                                                            

  7%|▋         | 40173/569592 [8:35:04<548:06:41,  3.73s/it]
  7%|▋         | 40174/569592 [8:35:08<534:35:50,  3.64s/it]
                                                            

  7%|▋         | 40174/569592 [8:35:08<534:35:50,  3.64s/it]
  7%|▋         | 40175/569592 [8:35:11<510:51:25,  3.47s/it]
                                                            

  7%|▋         | 40175/569592 [8:35:11<510:51:25,  3.47s/it]
  7%|▋         | 40176/569592 [8:35:12<398:04:51,  2.71s/it]
                                                            

  7%|▋         | 40176/569592 [8:35:12<398:04:51,  2.71s/it]
  7%|▋         | 40177/569592 [8:35:16<442:00:41,  3.01s/it]
                                                            

  7%|▋         | 40177/569592 [8:35:16<442:00:41,  3.01s/it]
  7%|▋         | 40178/569592 [8:35:17<352:08:20,  2.39s/it]
                                                            

  7%|▋         | 40178/569592 [8:35:17<352:08:20,  2.39s/it]
  7%|▋         | 40179/569592 [8:35:20<403:32:33,  2.74s/it]
                                                            

  7%|▋         | 40179/569592 [8:35:20<403:32:33,  2.74s/it]
  7%|▋         | 40180/569592 [8:35:21<325:17:34,  2.21s/it]
                                                            

  7%|▋         | 40180/569592 [8:35:21<325:17:34,  2.21s/it]
  7%|▋         | 40181/569592 [8:35:22<269:36:40,  1.83s/it]
                                                            

  7%|▋         | 40181/569592 [8:35:22<269:36:40,  1.83s/it]
  7%|▋         | 40182/569592 [8:35:26<348:07:43,  2.37s/it]
                                                            

  7%|▋         | 40182/569592 [8:35:26<348:07:43,  2.37s/it]
  7%|▋         | 40183/569592 [8:35:30<423:50:31,  2.88s/it]
                                                            

  7%|▋         | 40183/569592 [8:35:30<423:50:31,  2.88s/it]
  7%|▋         | 40184/569592 [8:35:33<451:52:12,  3.07s/it]
                                                            

  7%|▋         | 40184/569592 [8:35:33<451:52:12,  3.07s/it]
  7%|▋         | 40185/569592 [8:35:34<359:17:02,  2.44s/it]
                                                            

  7%|▋         | 40185/569592 [8:35:34<359:17:02,  2.44s/it]
  7%|▋         | 40186/569592 [8:35:38<427:34:26,  2.91s/it]
                                                            

  7%|▋         | 40186/569592 [8:35:38<427:34:26,  2.91s/it]
  7%|▋         | 40187/569592 [8:35:42<467:33:00,  3.18s/it]
                                                            

  7%|▋         | 40187/569592 [8:35:42<467:33:00,  3.18s/it]
  7%|▋         | 40188/569592 [8:35:43<368:13:29,  2.50s/it]
                                                            

  7%|▋         | 40188/569592 [8:35:43<368:13:29,  2.50s/it]
  7%|▋         | 40189/569592 [8:35:44<298:54:26,  2.03s/it]
                                                            

  7%|▋         | 40189/569592 [8:35:44<298:54:26,  2.03s/it]
  7%|▋         | 40190/569592 [8:35:48<402:07:42,  2.73s/it]
                                                            

  7%|▋         | 40190/569592 [8:35:48<402:07:42,  2.73s/it]
  7%|▋         | 40191/569592 [8:35:52<434:56:38,  2.96s/it]
                                                            

  7%|▋         | 40191/569592 [8:35:52<434:56:38,  2.96s/it]
  7%|▋         | 40192/569592 [8:35:55<441:27:54,  3.00s/it]
                                                            

  7%|▋         | 40192/569592 [8:35:55<441:27:54,  3.00s/it]
  7%|▋         | 40193/569592 [8:35:58<460:05:35,  3.13s/it]
                                                            

  7%|▋         | 40193/569592 [8:35:58<460:05:35,  3.13s/it]
  7%|▋         | 40194/569592 [8:35:59<362:52:17,  2.47s/it]
                                                            

  7%|▋         | 40194/569592 [8:35:59<362:52:17,  2.47s/it]
  7%|▋         | 40195/569592 [8:36:03<412:17:27,  2.80s/it]
                                                            

  7%|▋         | 40195/569592 [8:36:03<412:17:27,  2.80s/it]
  7%|▋         | 40196/569592 [8:36:04<336:35:21,  2.29s/it]
                                                            

  7%|▋         | 40196/569592 [8:36:04<336:35:21,  2.29s/it]
  7%|▋         | 40197/569592 [8:36:08<400:00:34,  2.72s/it]
                                                            

  7%|▋         | 40197/569592 [8:36:08<400:00:34,  2.72s/it]
  7%|▋         | 40198/569592 [8:36:11<427:38:47,  2.91s/it]
                                                            

  7%|▋         | 40198/569592 [8:36:11<427:38:47,  2.91s/it]
  7%|▋         | 40199/569592 [8:36:12<340:46:37,  2.32s/it]
                                                            

  7%|▋         | 40199/569592 [8:36:12<340:46:37,  2.32s/it]
  7%|▋         | 40200/569592 [8:36:16<415:13:52,  2.82s/it]
                                                            

  7%|▋         | 40200/569592 [8:36:16<415:13:52,  2.82s/it]
  7%|▋         | 40201/569592 [8:36:20<461:21:39,  3.14s/it]
                                                            

  7%|▋         | 40201/569592 [8:36:20<461:21:39,  3.14s/it]
  7%|▋         | 40202/569592 [8:36:23<458:03:00,  3.11s/it]
                                                            

  7%|▋         | 40202/569592 [8:36:23<458:03:00,  3.11s/it]
  7%|▋         | 40203/569592 [8:36:26<468:22:02,  3.19s/it]
                                                            

  7%|▋         | 40203/569592 [8:36:26<468:22:02,  3.19s/it]
  7%|▋         | 40204/569592 [8:36:30<478:36:36,  3.25s/it]
                                                            

  7%|▋         | 40204/569592 [8:36:30<478:36:36,  3.25s/it]
  7%|▋         | 40205/569592 [8:36:33<473:31:04,  3.22s/it]
                                                            

  7%|▋         | 40205/569592 [8:36:33<473:31:04,  3.22s/it]
  7%|▋         | 40206/569592 [8:36:39<622:08:31,  4.23s/it]
                                                            

  7%|▋         | 40206/569592 [8:36:39<622:08:31,  4.23s/it]
  7%|▋         | 40207/569592 [8:36:43<579:41:40,  3.94s/it]
                                                            

  7%|▋         | 40207/569592 [8:36:43<579:41:40,  3.94s/it]
  7%|▋         | 40208/569592 [8:36:46<541:51:57,  3.68s/it]
                                                            

  7%|▋         | 40208/569592 [8:36:46<541:51:57,  3.68s/it]
  7%|▋         | 40209/569592 [8:36:49<532:05:41,  3.62s/it]
                                                            

  7%|▋         | 40209/569592 [8:36:49<532:05:41,  3.62s/it]
  7%|▋         | 40210/569592 [8:36:50<412:07:53,  2.80s/it]
                                                            

  7%|▋         | 40210/569592 [8:36:50<412:07:53,  2.80s/it]
  7%|▋         | 40211/569592 [8:36:54<452:29:14,  3.08s/it]
                                                            

  7%|▋         | 40211/569592 [8:36:54<452:29:14,  3.08s/it]
  7%|▋         | 40212/569592 [8:36:58<487:38:50,  3.32s/it]
                                                            

  7%|▋         | 40212/569592 [8:36:58<487:38:50,  3.32s/it]
  7%|▋         | 40213/569592 [8:37:01<505:35/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (101754940 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
:57,  3.44s/it]
                                                            

  7%|▋         | 40213/569592 [8:37:01<505:35:57,  3.44s/it]
  7%|▋         | 40214/569592 [8:37:05<505:31:53,  3.44s/it]
                                                            

  7%|▋         | 40214/569592 [8:37:05<505:31:53,  3.44s/it]
  7%|▋         | 40215/569592 [8:37:06<398:01:34,  2.71s/it]
                                                            

  7%|▋         | 40215/569592 [8:37:06<398:01:34,  2.71s/it]
  7%|▋         | 40216/569592 [8:37:07<319:58:00,  2.18s/it]
                                                            

  7%|▋         | 40216/569592 [8:37:07<319:58:00,  2.18s/it]
  7%|▋         | 40217/569592 [8:37:11<405:34:43,  2.76s/it]
                                                            

  7%|▋         | 40217/569592 [8:37:11<405:34:43,  2.76s/it]
  7%|▋         | 40218/569592 [8:37:15<452:04:13,  3.07s/it]
                                                            

  7%|▋         | 40218/569592 [8:37:15<452:04:13,  3.07s/it]
  7%|▋         | 40219/569592 [8:37:18<459:00:36,  3.12s/it]
                                                            

  7%|▋         | 40219/569592 [8:37:18<459:00:36,  3.12s/it]
  7%|▋         | 40220/569592 [8:37:19<362:08:21,  2.46s/it]
                                                            

  7%|▋         | 40220/569592 [8:37:19<362:08:21,  2.46s/it]
  7%|▋         | 40221/569592 [8:37:20<295:50:14,  2.01s/it]
                                                            

  7%|▋         | 40221/569592 [8:37:20<295:50:14,  2.01s/it]
  7%|▋         | 40222/569592 [8:37:21<248:59:45,  1.69s/it]
                                                            

  7%|▋         | 40222/569592 [8:37:21<248:59:45,  1.69s/it]
  7%|▋         | 40223/569592 [8:37:25<372:08:25,  2.53s/it]
                                                            

  7%|▋         | 40223/569592 [8:37:25<372:08:25,  2.53s/it]
  7%|▋         | 40224/569592 [8:37:26<309:12:24,  2.10s/it]
                                                            

  7%|▋         | 40224/569592 [8:37:26<309:12:24,  2.10s/it]
  7%|▋         | 40225/569592 [8:37:27<258:17:42,  1.76s/it]
                                                            

  7%|▋         | 40225/569592 [8:37:27<258:17:42,  1.76s/it]
  7%|▋         | 40226/569592 [8:37:31<335:15:52,  2.28s/it]
                                                            

  7%|▋         | 40226/569592 [8:37:31<335:15:52,  2.28s/it]
  7%|▋         | 40227/569592 [8:37:32<276:03:57,  1.88s/it]
                                                            

  7%|▋         | 40227/569592 [8:37:32<276:03:57,  1.88s/it]
  7%|▋         | 40228/569592 [8:37:35<343:23:50,  2.34s/it]
                                                            

  7%|▋         | 40228/569592 [8:37:35<343:23:50,  2.34s/it]
  7%|▋         | 40229/569592 [8:37:39<389:26:24,  2.65s/it]
                                                            

  7%|▋         | 40229/569592 [8:37:39<389:26:24,  2.65s/it]
  7%|▋         | 40230/569592 [8:37:40<317:06:22,  2.16s/it]
                                                            

  7%|▋         | 40230/569592 [8:37:40<317:06:22,  2.16s/it]
  7%|▋         | 40231/569592 [8:37:40<262:55:28,  1.79s/it]
                                                            

  7%|▋         | 40231/569592 [8:37:40<262:55:28,  1.79s/it]
  7%|▋         | 40232/569592 [8:37:44<355:48:14,  2.42s/it]
                                                            

  7%|▋         | 40232/569592 [8:37:44<355:48:14,  2.42s/it]
  7%|▋         | 40233/569592 [8:37:48<417:48:27,  2.84s/it]
                                                            

  7%|▋         | 40233/569592 [8:37:48<417:48:27,  2.84s/it]
  7%|▋         | 40234/569592 [8:37:51<435:23:23,  2.96s/it]
                                                            

  7%|▋         | 40234/569592 [8:37:51<435:23:23,  2.96s/it]
  7%|▋         | 40235/569592 [8:37:52<351:46:13,  2.39s/it]
                                                            

  7%|▋         | 40235/569592 [8:37:52<351:46:13,  2.39s/it]
  7%|▋         | 40236/569592 [8:37:57<434:54:25,  2.96s/it]
                                                            

  7%|▋         | 40236/569592 [8:37:57<434:54:25,  2.96s/it]
  7%|▋         | 40237/569592 [8:37:58<346:55:54,  2.36s/it]
                                                            

  7%|▋         | 40237/569592 [8:37:58<346:55:54,  2.36s/it]
  7%|▋         | 40238/569592 [8:38:02<432:36:57,  2.94s/it]
                                                            

  7%|▋         | 40238/569592 [8:38:02<432:36:57,  2.94s/it]
  7%|▋         | 40239/569592 [8:38:03<345:14:13,  2.35s/it]
                                                            

  7%|▋         | 40239/569592 [8:38:03<345:14:13,  2.35s/it]
  7%|▋         | 40240/569592 [8:38:07<414:23:57,  2.82s/it]
                                                            

  7%|▋         | 40240/569592 [8:38:07<414:23:57,  2.82s/it]
  7%|▋         | 40241/569592 [8:38:08<331:05:22,  2.25s/it]
                                                            

  7%|▋         | 40241/569592 [8:38:08<331:05:22,  2.25s/it]
  7%|▋         | 40242/569592 [8:38:09<273:43:48,  1.86s/it]
                                                            

  7%|▋         | 40242/569592 [8:38:09<273:43:48,  1.86s/it]
  7%|▋         | 40243/569592 [8:38:10<233:38:36,  1.59s/it]
                                                            

  7%|▋         | 40243/569592 [8:38:10<233:38:36,  1.59s/it]
  7%|▋         | 40244/569592 [8:38:13<318:53:12,  2.17s/it]
                                                            

  7%|▋         | 40244/569592 [8:38:13<318:53:12,  2.17s/it]
  7%|▋         | 40245/569592 [8:38:14<268:14:51,  1.82s/it]
                                                            

  7%|▋         | 40245/569592 [8:38:14<268:14:51,  1.82s/it]
  7%|▋         | 40246/569592 [8:38:16<282:22:41,  1.92s/it]
                                                            

  7%|▋         | 40246/569592 [8:38:16<282:22:41,  1.92s/it]
  7%|▋         | 40247/569592 [8:38:20<371:32:17,  2.53s/it]
                                                            

  7%|▋         | 40247/569592 [8:38:20<371:32:17,  2.53s/it]
  7%|▋         | 40248/569592 [8:38:24<431:53:55,  2.94s/it]
                                                            

  7%|▋         | 40248/569592 [8:38:24<431:53:55,  2.94s/it]
  7%|▋         | 40249/569592 [8:38:28<465:49:08,  3.17s/it]
                                                            

  7%|▋         | 40249/569592 [8:38:28<465:49:08,  3.17s/it]
  7%|▋         | 40250/569592 [8:38:29<367:00:07,  2.50s/it]
                                                            

  7%|▋         | 40250/569592 [8:38:29<367:00:07,  2.50s/it]
  7%|▋         | 40251/569592 [8:38:32<409:51:40,  2.79s/it]
                                                            

  7%|▋         | 40251/569592 [8:38:32<409:51:40,  2.79s/it]
  7%|▋         | 40252/569592 [8:38:37<498:00:04,  3.39s/it]
                                                            

  7%|▋         | 40252/569592 [8:38:37<498:00:04,  3.39s/it]
  7%|▋         | 40253/569592 [8:38:41<508:32:22,  3.46s/it]
                                                            

  7%|▋         | 40253/569592 [8:38:41<508:32:22,  3.46s/it]
  7%|▋         | 40254/569592 [8:38:44<500:14:57,  3.40s/it]
                                                            

  7%|▋         | 40254/569592 [8:38:44<500:14:57,  3.40s/it]
  7%|▋         | 40255/569592 [8:38:48<503:43:33,  3.43s/it]
                                                            

  7%|▋         | 40255/569592 [8:38:48<503:43:33,  3.43s/it]
  7%|▋         | 40256/569592 [8:38:51<505:29:07,  3.44s/it]
                                                            

  7%|▋         | 40256/569592 [8:38:51<505:29:07,  3.44s/it]
  7%|▋         | 40257/569592 [8:38:52<394:01:19,  2.68s/it]
                                                            

  7%|▋         | 40257/569592 [8:38:52<394:01:19,  2.68s/it]
  7%|▋         | 40258/569592 [8:38:55<418:22:05,  2.85s/it]
                                                            

  7%|▋         | 40258/569592 [8:38:55<418:22:05,  2.85s/it]
  7%|▋         | 40259/569592 [8:38:59<447:35:56,  3.04s/it]
                                                            

  7%|▋         | 40259/569592 [8:38:59<447:35:56,  3.04s/it]
  7%|▋         | 40260/569592 [8:39:02<458:21:48,  3.12s/it]
                                                            

  7%|▋         | 40260/569592 [8:39:02<458:21:48,  3.12s/it]
  7%|▋         | 40261/569592 [8:39:03<362:03:08,  2.46s/it]
                                                            

  7%|▋         | 40261/569592 [8:39:03<362:03:08,  2.46s/it]
  7%|▋         | 40262/569592 [8:39:06<404:45:40,  2.75s/it]
                                                            

  7%|▋         | 40262/569592 [8:39:06<404:45:40,  2.75s/it]
  7%|▋         | 40263/569592 [8:39:10<425:39:02,  2.89s/it]
                                                            

  7%|▋         | 40263/569592 [8:39:10<425:39:02,  2.89s/it]
  7%|▋         | 40264/569592 [8:39:13<446:14:22,  3.03s/it]
                                                            

  7%|▋         | 40264/569592 [8:39:13<446:14:22,  3.03s/it]
  7%|▋         | 40265/569592 [8:39:16<464:38:10,  3.16s/it]
                                                            

  7%|▋         | 40265/569592 [8:39:16<464:38:10,  3.16s/it]
  7%|▋         | 40266/569592 [8:39:17<366:52:23,  2.50s/it]
                                                            

  7%|▋         | 40266/569592 [8:39:17<366:52:23,  2.50s/it]
  7%|▋         | 40267/569592 [8:39:21<414:26:30,  2.82s/it]
                                                            

  7%|▋         | 40267/569592 [8:39:21<414:26:30,  2.82s/it]
  7%|▋         | 40268/569592 [8:39:22<333:12:13,  2.27s/it]
                                                            

  7%|▋         | 40268/569592 [8:39:22<333:12:13,  2.27s/it]
  7%|▋         | 40269/569592 [8:39:25<382:17:36,  2.60s/it]
                                                            

  7%|▋         | 40269/569592 [8:39:25<382:17:36,  2.60s/it]
  7%|▋         | 40270/569592 [8:39:28<413:00:09,  2.81s/it]
                                                            

  7%|▋         | 40270/569592 [8:39:29<413:00:09,  2.81s/it]
  7%|▋         | 40271/569592 [8:39:29<331:40:17,  2.26s/it]
                                                            

  7%|▋         | 40271/569592 [8:39:29<331:40:17,  2.26s/it]
  7%|▋         | 40272/569592 [8:39:33<377:20:20,  2.57s/it]
                                                            

  7%|▋         | 40272/569592 [8:39:33<377:20:20,  2.57s/it]
  7%|▋         | 40273/569592 [8:39:37<433:26:03,  2.95s/it]
                                                            

  7%|▋         | 40273/569592 [8:39:37<433:26:03,  2.95s/it]
  7%|▋         | 40274/569592 [8:39:38<347:11:27,  2.36s/it]
                                                            

  7%|▋         | 40274/569592 [8:39:38<347:11:27,  2.36s/it]
  7%|▋         | 40275/569592 [8:39:39<285:50:35,  1.94s/it]
                                                            

  7%|▋         | 40275/569592 [8:39:39<285:50:35,  1.94s/it]
  7%|▋         | 40276/569592 [8:39:42<363:13:21,  2.47s/it]
                                                            

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  7%|▋         | 40294/569592 [8:40:42<399:05:44,  2/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (97635370 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
.71s/it]
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  7%|▋         | 40474/569592 [8:48:45<484:13:12,  3.29s/it]
                                                            

  7%|�/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (91307000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
��         | 40474/569592 [8:48:45<484:13:12,  3.29s/it]
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  7%|▋         | 40480/56/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (96787200 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
9592 [8:48:57<275:23:36,  1.87s/it]
                                                            

  7%|▋         | 40480/569592 [8:48:58<275:23:36,  1.87s/it]
  7%|▋         | 40481/569592 [8:49:01<358:53:11,  2.44s/it]
                                                            

  7%|▋         | 40481/569592 [8:49:01<358:53:11,  2.44s/it]
  7%|▋         | 40482/569592 [8:49:02<298:36:59,  2.03s/it]
                                                            

  7%|▋         | 40482/569592 [8:49:02<298:36:59,  2.03s/it]
  7%|▋         | 40483/569592 [8:49:07<398:06:52,  2.71s/it]
                                                            

  7%|▋         | 40483/569592 [8:49:07<398:06:52,  2.71s/it]
  7%|▋         | 40484/569592 [8:49:08<320:56:06,  2.18s/it]
                                                            

  7%|▋         | 40484/569592 [8:49:08<320:56:06,  2.18s/it]
  7%|▋         | 40485/569592 [8:49:11<387:49:32,  2.64s/it]
                                                            

  7%|▋         | 40485/569592 [8:49:11<387:49:32,  2.64s/it]
  7%|▋         | 40486/569592 [8:49:12<315:49:18,  2.15s/it]
                                                            

  7%|▋         | 40486/569592 [8:49:12<315:49:18,  2.15s/it]
  7%|▋         | 40487/569592 [8:49:17<425:51:35,  2.90s/it]
                                                            

  7%|▋         | 40487/569592 [8:49:17<425:51:35,  2.90s/it]
  7%|▋         | 40488/569592 [8:49:18<340:46:57,  2.32s/it]
                                                            

  7%|▋         | 40488/569592 [8:49:18<340:46:57,  2.32s/it]
  7%|▋         | 40489/569592 [8:49:21<385:42:44,  2.62s/it]
                                                            

  7%|▋         | 40489/569592 [8:49:21<385:42:44,  2.62s/it]
  7%|▋         | 40490/569592 [8:49:25<433:57:57,  2.95s/it]
                                                            

  7%|▋         | 40490/569592 [8:49:25<433:57:57,  2.95s/it]
  7%|▋         | 40491/569592 [8:49:30<505:32:29,  3.44s/it]
                                                            

  7%|▋         | 40491/569592 [8:49:30<505:32:29,  3.44s/it]
  7%|▋         | 40492/569592 [8:49:30<396:24:57,  2.70s/it]
                                                            

  7%|▋         | 40492/569592 [8:49:31<396:24:57,  2.70s/it]
  7%|▋         | 40493/569592 [8:49:31<321:32:36,  2.19s/it]
                                                            

  7%|▋         | 40493/569592 [8:49:32<321:32:36,  2.19s/it]
  7%|▋         | 40494/569592 [8:49:32<268:02:44,  1.82s/it]
                                                            

  7%|▋         | 40494/569592 [8:49:32<268:02:44,  1.82s/it]
  7%|▋         | 40495/569592 [8:49:37<392:50:16,  2.67s/it]
                                                            

  7%|▋         | 40495/569592 [8:49:37<392:50:16,  2.67s/it]
  7%|▋         | 40496/569592 [8:49:38<329:48:52,  2.24s/it]
                                                            

  7%|▋         | 40496/569592 [8:49:38<329:48:52,  2.24s/it]
  7%|▋         | 40497/569592 [8:49:42<393:08:10,  2.67s/it]
                                                            

  7%|▋         | 40497/569592 [8:49:42<393:08:10,  2.67s/it]
  7%|▋         | 40498/569592 [8:49:46<428:18:51,  2.91s/it]
                                                            

  7%|▋         | 40498/569592 [8:49:46<428:18:51,  2.91s/it]
  7%|▋         | 40499/569592 [8:49:47<367:44:09,  2.50s/it]
                                                            

  7%|▋         | 40499/569592 [8:49:47<367:44:09,  2.50s/it]
  7%|▋         | 40500/569592 [8:49:51<420:11:32,  2.86s/it]
                                                            

  7%|▋         | 40500/569592 [8:49:51<420:11:32,  2.86s/it]
  7%|▋         | 40501/569592 [8:49:54<449:00:17,  3.06s/it]
                                                            

  7%|▋         | 40501/569592 [8:49:54<449:00:17,  3.06s/it]
  7%|▋         | 40502/569592 [8:49:58<466:06:17,  3.17s/it]
                                                            

  7%|▋         | 40502/569592 [8:49:58<466:06:17,  3.17s/it]
  7%|▋         | 40503/569592 [8:49:59<368:10:36,  2.51s/it]
                                                            

  7%|▋         | 40503/569592 [8:49:59<368:10:36,  2.51s/it]
  7%|▋         | 40504/569592 [8:50:02<398:25:21,  2.71s/it]
                                                            

  7%|▋         | 40504/569592 [8:50:02<398:25:21,  2.71s/it]
  7%|▋         | 40505/569592 [8:50:03<321:07:07,  2.18s/it]
                                                            

  7%|▋         | 40505/569592 [8:50:03<321:07:07,  2.18s/it]
  7%|▋         | 40506/569592 [8:50:06<370:03:19,  2.52s/it]
                                                            

  7%|▋         | 40506/569592 [8:50:06<370:03:19,  2.52s/it]
  7%|▋         | 40507/569592 [8:50:10<411:30:01,  2.80s/it]
                                                            

  7%|▋         | 40507/569592 [8:50:10<411:30:01,  2.80s/it]
  7%|▋         | 40508/569592 [8:50:14<462:46:43,  3.15s/it]
                                                            

  7%|▋         | 40508/569592 [8:50:14<462:46:43,  3.15s/it]
  7%|▋         | 40509/569592 [8:50:17<467:38:18,  3.18s/it]
                                                            

  7%|▋         | 40509/569592 [8:50:17<467:38:18,  3.18s/it]
  7%|▋         | 40510/569592 [8:50:20<467:36:50,  3.18s/it]
                                                            

  7%|▋         | 40510/569592 [8:50:20<467:36:50,  3.18s/it]
  7%|▋         | 40511/569592 [8:50:23<472:59:40,  3.22s/it]
                                                            

  7%|▋         | 40511/569592 [8:50:23<472:59:40,  3.22s/it]
  7%|▋         | 40512/569592 [8:50:24<371:00:13,  2.52s/it]
                                                            

  7%|▋         | 40512/569592 [8:50:24<371:00:13,  2.52s/it]
  7%|▋         | 40513/569592 [8:50:28<432:40:44,  2.94s/it]
                                                            

  7%|▋         | 40513/569592 [8:50:28<432:40:44,  2.94s/it]
  7%|▋         | 40514/569592 [8:50:31<440:50:30,  3.00s/it]
                                                            

  7%|▋         | 40514/569592 [8:50:31<440:50:30,  3.00s/it]
  7%|▋         | 40515/569592 [8:50:35<475:54:18,  3.24s/it]
                                                            

  7%|▋         | 40515/569592 [8:50:35<475:54:18,  3.24s/it]
  7%|▋         | 40516/569592 [8:50:39<489:28:46,  3.33s/it]
                                                            

  7%|▋         | 40516/569592 [8:50:39<489:28:46,  3.33s/it]
  7%|▋         | 40517/569592 [8:50:43<546:26:44,  3.72s/it]
                                                            

  7%|▋         | 40517/569592 [8:50:43<546:26:44,  3.72s/it]
  7%|▋         | 40518/569592 [8:50:48<606:27:38,  4.13s/it]
                                                            

  7%|▋         | 40518/569592 [8:50:48<606:27:38,  4.13s/it]
  7%|▋         | 40519/569592 [8:50:51<566:26:39,  3.85s/it]
                                                            

  7%|▋         | 40519/569592 [8:50:51<566:26:39,  3.85s/it]
  7%|▋         | 40520/569592 [8:50:55<558:41:06,  3.80s/it]
                                                            

  7%|▋         | 40520/569592 [8:50:55<558:41:06,  3.80s/it]
  7%|▋         | 40521/569592 [8:50:59<553:16:52,  3.76s/it]
                                                            

  7%|▋         | 40521/569592 [8:50:59<553:16:52,  3.76s/it]
  7%|▋         | 40522/569592 [8:51:02<540:05:49,  3.68s/it]
                                                            

  7%|▋         | 40522/569592 [8:51:02<540:05:49,  3.68s/it]
  7%|▋         | 40523/569592 [8:51:07<582:39:38,  3.96s/it]
                                                            

  7%|▋         | 40523/569592 [8:51:07<582:39:38,  3.96s/it]
  7%|▋         | 40524/569592 [8:51:11<577:32:28,  3.93s/it]
                                                            

  7%|▋         | 40524/569592 [8:51:11<577:32:28,  3.93s/it]
  7%|▋         | 40525/569592 [8:51:14<552:20:25,  3.76s/it]
                                                            

  7%|▋         | 40525/569592 [8:51:14<552:20:25,  3.76s/it]
  7%|▋         | 40526/569592 [8:51:18<537:15:21,  3.66s/it]
                                                            

  7%|▋         | 40526/569592 [8:51:18<537:15:21,  3.66s/it]
  7%|▋         | 40527/569592 [8:51:19<421:02:10,  2.86s/it]
                                                            

  7%|▋         | 40527/569592 [8:51:19<421:02:10,  2.86s/it]
  7%|▋         | 40528/569592 [8:51:22<447:59:11,  3.05s/it]
                                                            

  7%|▋         | 40528/569592 [8:51:22<447:59:11,  3.05s/it]
  7%|▋         | 40529/569592 [8:51:25<463:47:10,  3.16s/it]
                                                            

  7%|▋         | 40529/569592 [8:51:25<463:47:10,  3.16s/it]
  7%|▋         | 40530/569592 [8:51:29<471:48:38,  3.21s/it]
                                                            

  7%|▋         | 40530/569592 [8:51:29<471:48:38,  3.21s/it]
  7%|▋         | 40531/569592 [8:51:32<484:12:44,  3.29s/it]
                                                            

  7%|▋         | 40531/569592 [8:51:32<484:12:44,  3.29s/it]
  7%|▋         | 40532/569592 [8:51:35<473:35:42,  3.22s/it]
                                                            

  7%|▋         | 40532/569592 [8:51:35<473:35:42,  3.22s/it]
  7%|▋         | 40533/569592 [8:51:36<371:54:29,  2.53s/it]
                                                            

  7%|▋         | 40533/569592 [8:51:36<371:54:29,  2.53s/it]
  7%|▋         | 40534/569592 [8:51:37<302:16:12,  2.06s/it]
                                                            

  7%|▋         | 40534/569592 [8:51:37<302:16:12,  2.06s/it]
  7%|▋         | 40535/569592 [8:51:38<260:38:59,  1.77s/it]
                                                            

  7%|▋         | 40535/569592 [8:51:38<260:38:59,  1.77s/it]
  7%|▋         | 40536/569592 [8:51:42<343:09:59,  2.34s/it]
                                                            

  7%|▋         | 40536/569592 [8:51:42<343:09:59,  2.34s/it]
  7%|▋         | 40537/569592 [8:51:46<411:50:34,  2.80s/it]
                                                            

  7%|▋         | 40537/569592 [8:51:46<411:50:34,  2.80s/it]
  7%|▋         | 40538/569592 [8:51:50<452:17:03,  3.08s/it]
                                                            

  7%|▋         | 40538/569592 [8:51:50<452:17:03,  3.08s/it]
  7%|▋         | 40539/569592 [8:51:53<484:48:52,  3.30s/it]
                                                            

  7%|▋         | 40539/569592 [8:51:53<484:48:52,  3.30s/it]
  7%|▋         | 40540/569592 [8:51:57<479:55:30,  3.27s/it]
                                                            

  7%|▋         | 40540/569592 [8:51:57<479:55:30,  3.27s/it]
  7%|▋         | 40541/569592 [8:52:00<485:00:36,  3.30s/it]
                                                            

  7%|▋         | 40541/569592 [8:52:00<485:00:36,  3.30s/it]
  7%|▋         | 40542/569592 [8:52:01<379:26:59,  2.58s/it]
                                                            

  7%|▋         | 40542/569592 [8:52:01<379:26:59,  2.58s/it]
  7%|▋         | 40543/569592 [8:52:04<424:47:37,  2.89s/it]
                                                            

  7%|▋         | 40543/569592 [8:52:05<424:47:37,  2.89s/it]
  7%|▋         | 40544/569592 [8:52:08<462:08:16,  3.14s/it]
                                                            

  7%|▋         | 40544/569592 [8:52:08<462:08:16,  3.14s/it]
  7%|▋         | 40545/569592 [8:52:09<366:41:01,  2.50s/it]
                                                            

  7%|▋         | 40545/569592 [8:52:09<366:41:01,  2.50s/it]
  7%|▋         | 40546/569592 [8:52:12<392:46:23,  2.67s/it]
                                                            

  7%|▋         | 40546/569592 [8:52:13<392:46:23,  2.67s/it]
  7%|▋         | 40547/569592 [8:52:16<431:18:45,  2.93s/it]
                                                            

  7%|▋         | 40547/569592 [8:52:16<431:18:45,  2.93s/it]
  7%|▋         | 40548/569592 [8:52:20<503:34:50,  3.43s/it]
                                                            

  7%|▋         | 40548/569592 [8:52:20<503:34:50,  3.43s/it]
  7%|▋         | 40549/569592 [8:52:21<391:29:41,  2.66s/it]
                                                            

  7%|▋         | 40549/569592 [8:52:21<391:29:41,  2.66s/it]
  7%|▋         | 40550/569592 [8:52:25<435:21:24,  2.96s/it]
                                                            

  7%|▋         | 40550/569592 [8:52:25<435:21:24,  2.96s/it]
  7%|▋         | 40551/569592 [8:52:29<482:42:43,  3.28s/it]
                                                            

  7%|▋         | 40551/569592 [8:52:29<482:42:43,  3.28s/it]
  7%|▋         | 40552/569592 [8:52:32<469:42:38,  3.20s/it]
                                                            

  7%|▋         | 40552/569592 [8:52:32<469:42:38,  3.20s/it]
  7%|▋         | 40553/569592 [8:52:35<469:39:46,  3.20s/it]
                                                            

  7%|▋         | 40553/569592 [8:52:35<469:39:46,  3.20s/it]
  7%|▋         | 40554/569592 [8:52:36<370:42:01,  2.52s/it]
                                                            

  7%|▋         | 40554/569592 [8:52:36<370:42:01,  2.52s/it]
  7%|▋         | 40555/569592 [8:52:40<419:59:19,  2.86s/it]
                                                            

  7%|▋         | 40555/569592 [8:52:40<419:59:19,  2.86s/it]
  7%|▋         | 40556/569592 [8:52:43<442:19:06,  3.01s/it]
                                                            

  7%|▋         | 40556/569592 [8:52:43<442:19:06,  3.01s/it]
  7%|▋         | 40557/569592 [8:52:44<351:44:35,  2.39s/it]
                                                            

  7%|▋         | 40557/569592 [8:52:44<351:44:35,  2.39s/it]
  7%|▋         | 40558/569592 [8:52:45<288:24:26,  1.96s/it]
                                                            

  7%|▋         | 40558/569592 [8:52:45<288:24:26,  1.96s/it]
  7%|▋         | 40559/569592 [8:52:49<359:24:57,  2.45s/it]
                                                            

  7%|▋         | 40559/569592 [8:52:49<359:24:57,  2.45s/it]
  7%|▋         | 40560/569592 [8:52:50<293:57:03,  2.00s/it]
                                                            

  7%|▋         | 40560/569592 [8:52:50<293:57:03,  2.00s/it]
  7%|▋         | 40561/569592 [8:52:51<247:12:32,  1.68s/it]
                                                            

  7%|▋         | 40561/569592 [8:52:51<247:12:32,  1.68s/it]
  7%|▋         | 40562/569592 [8:52:55<348:52:17,  2.37s/it]
                                                            

  7%|▋         | 40562/569592 [8:52:55<348:52:17,  2.37s/it]
  7%|▋         | 40563/569592 [8:52:55<285:52:05,  1.95s/it]
                                                            

  7%|▋         | 40563/569592 [8:52:55<285:52:05,  1.95s/it]
  7%|▋         | 40564/569592 [8:52:59<346:16:38,  2.36s/it]
                                                            

  7%|▋         | 40564/569592 [8:52:59<346:16:38,  2.36s/it]
  7%|▋         | 40565/569592 [8:53:03<413:52:01,  2.82s/it]
                                                            

  7%|▋         | 40565/569592 [8:53:03<413:52:01,  2.82s/it]
  7%|▋         | 40566/569592 [8:53:07<468:15:37,  3.19s/it]
                                                            

  7%|▋         | 40566/569592 [8:53:07<468:15:37,  3.19s/it]
  7%|▋         | 40567/569592 [8:53:11<504:21:48,  3.43s/it]
                                                            

  7%|▋         | 40567/569592 [8:53:11<504:21:48,  3.43s/it]
  7%|▋         | 40568/569592 [8:53:12<393:32:25,  2.68s/it]
                                                            

  7%|▋         | 40568/569592 [8:53:12<393:32:25,  2.68s/it]
  7%|▋         | 40569/569592 [8:53:13<317:13:56,  2.16s/it]
                                                            

  7%|▋         | 40569/569592 [8:53:13<317:13:56,  2.16s/it]
  7%|▋         | 40570/569592 [8:53:14<264:54:25,  1.80s/it]
                                                            

  7%|▋         | 40570/569592 [8:53:14<264:54:25,  1.80s/it]
  7%|▋         | 40571/569592 [8:53:17<332:30:48,  2.26s/it]
                                                            

  7%|▋         | 40571/569592 [8:53:17<332:30:48,  2.26s/it]
  7%|▋         | 40572/569592 [8:53:21<400:31:04,  2.73s/it]
                                                            

  7%|▋         | 40572/569592 [8:53:21<400:31:04,  2.73s/it]
  7%|▋         | 40573/569592 [8:53:22<322:43:19,  2.20s/it]
                                                            

  7%|▋         | 40573/569592 [8:53:22<322:43:19,  2.20s/it]
  7%|▋         | 40574/569592 [8:53:23<267:22:37,  1.82s/it]
                                                            

  7%|▋         | 40574/569592 [8:53:23<267:22:37,  1.82s/it]
  7%|▋         | 40575/569592 [8:53:24<228:45:13,  1.56s/it]
                                                            

  7%|▋         | 40575/569592 [8:53:24<228:45:13,  1.56s/it]
  7%|▋         | 40576/569592 [8:53:27<333:10:33,  2.27s/it]
                                                            

  7%|▋         | 40576/569592 [8:53:27<333:10:33,  2.27s/it]
  7%|▋         | 40577/569592 [8:53:28<274:44:30,  1.87s/it]
                                                            

  7%|▋         | 40577/569592 [8:53:28<274:44:30,  1.87s/it]
  7%|▋         | 40578/569592 [8:53:29<234:05:07,  1.59s/it]
                                                            

  7%|▋         | 40578/569592 [8:53:29<234:05:07,  1.59s/it]
  7%|▋         | 40579/569592 [8:53:33<319:42:42,  2.18s/it]
                                                            

  7%|▋         | 40579/569592 [8:53:33<319:42:42,  2.18s/it]
  7%|▋         | 40580/569592 [8:53:34<278:50:43,  1.90s/it]
                                                            

  7%|▋         | 40580/569592 [8:53:34<278:50:43,  1.90s/it]
  7%|▋         | 40581/569592 [8:53:38<383:03:57,  2.61s/it]
                                                            

  7%|▋         | 40581/569592 [8:53:38<383:03:57,  2.61s/it]
  7%|▋         | 40582/569592 [8:53:43<479:06:32,  3.26s/it]
                                                            

  7%|▋         | 40582/569592 [8:53:43<479:06:32,  3.26s/it]
  7%|▋         | 40583/569592 [8:53:47<486:49:25,  3.31s/it]
                                                            

  7%|▋         | 40583/569592 [8:53:47<486:49:25,  3.31s/it]
  7%|▋         | 40584/569592 [8:53:48<382:59:49,  2.61s/it]
                                                            

  7%|▋         | 40584/569592 [8:53:48<382:59:49,  2.61s/it]
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  7%|▋       /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (92693546 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
  | 40589/569592 [8:53:59<396:45:12,  2.70s/it]
                                                            

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  7%|▋         | 40627/569592 [8:55:4/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (94618368 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
5<473:16:07,  3.22s/it]
                                                            

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  7%|▋         | 406/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
70/569592 [8:57:56<453:25:42,  3.09s/it]
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                        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (92846400 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                    

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  7%|▋         | 40768/56959/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
2 [9:02:21<505:15:58,  3.44s/it]
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                                /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                            

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  7%|▋         | 40817/569592 [9/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95951213 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
:04:23<427:35:04,  2.91s/it]
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  7%|▋      /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
   | 40828/569592 [9:04:49<337:26:55,  2.30s/it]
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                                                            /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(


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  7%|�/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (105212640 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
��         | 40986/569592 [9:11:56<463:10:09,  3.15s/it]
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  7%|▋         | 41000/569592 [9:12:41<499:14:23,  3.40s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-41000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-41000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-41000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-41000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-41000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-41000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-40000] due to args.save_total_limit

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  7%|▋         | 41038/569592 [9:16:36<364:20:03,  2.48s/it/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
]
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  warnings.warn(
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  7%|▋         | 41158/5695/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
92 [9:22:02<280:10:57,  1.91s/it]
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  7%|▋ /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95971008 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
        | 41169/569592 [9:22:29<296:45:10,  2.02s/it]
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  7%|▋     /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90206000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  warnings.warn(
89:49:04,  3.34s/it]
                                                            

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 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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                                           /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (102848332 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                 

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  warnings.warn(
9:18,  2.92s/it]
                                                            

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       /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                     

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  warnings.warn(
.84s/it]
                                                            

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  7%|▋      /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100128768 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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                                   /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                         

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  7%|▋         | 41687/56959/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (94214448 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
2 [9:46:06<517:51:52,  3.53s/it]
                                                            

  7%|▋         | 41687/569592 [9:46:06<517:51:52,  3.53s/it]
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  7%|▋         | 41698/569592 [9:46:30<341:35:27,  2.33s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

                                                            

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                                                   /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (96310668 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
         

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                                           /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                 

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  7%|▋         | 42000/569592 [10:00:02<364:15:18,  2.49s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-42000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-42000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-42000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-42000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-42000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-42000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-41000] due to args.save_total_limit

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  7%|▋         | 42006/569592 [10:02:24<1392:19:52,/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
  9.50s/it]
                                                              

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              /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90316800 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                               

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  7%|▋         | 42081/569592 [10:05:59<292:27:57,  2.0/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (108000000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
0s/it]
                                                             

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  7%|▋         | 42183/569592/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (101518284 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 [10:10:52<363:45:00,  2.48s/it]
                                                             

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  7%|▋  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
       | 42226/569592 [10:12:38<321:42:46,  2.20s/it]
                                                             

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  7%|▋         | 42252/569592 [10:1/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
3:55<435:44:41,  2.97s/it]
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  7%|▋         | 42/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
301/569592 [10:16:09<361:24:29,  2.47s/it]
                                                             

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  7%|▋         | 42306/569592 [10:16:25<422:10:23,  2.88s/it]
                                                             

  7%|▋         | 42306/569592 [10:16:25<422:10:23,  2.88s/it]
  7%|▋         | 42307/569592 [10:16:28<429:54:01,  2.94s/it]
                                                             

  7%|▋         | 42307/569592 [10:16:28<429:54:01,  2.94s/it]
  7%|▋         | 42308/569592 [10:16:29<344:38:16,  2.35s/it]
                                                             

  7%|▋         | 42308/569592 [10:16:29<344:38:16,  2.35s/it]
  7%|▋         | 42309/569592 [10:16:30<286:02:21,  1.95s/it]
                                                             

  7%|▋         | 42309/569592 [10:16:30<286:02:21,  1.95s/it]
  7%|▋         | 42310/569592 [10:16:34<349:42:58,  2.39s/it]
                                                             

  7%|▋         | 42310/569592 [10:16:34<349:42:58,  2.39s/it]
  7%|▋         | 42311/569592 [10:16:37<413:14:06,  2.82s/it]
                                                             

  7%|▋         | 42311/569592 [10:16:37<413:14:06,  2.82s/it]
  7%|▋         | 42312/569592 [10:16:38<330:32:33,  2.26s/it]
                                                             

  7%|▋         | 42312/569592 [10:16:38<330:32:33,  2.26s/it]
  7%|▋         | 42313/569592 [10:16:39<272:46:17,  1.86s/it]
                                                             

  7%|▋         | 42313/569592 [10:16:39<272:46:17,  1.86s/it]
  7%|▋         | 42314/569592 [10:16:40<232:02:38,  1.58s/it]
                                                             

  7%|▋         | 42314/569592 [10:16:40<232:02:38,  1.58s/it]
  7%|▋         | 42315/569592 [10:16:44<322:54:35,  2.20s/it]
                                                             

  7%|▋         | 42315/569592 [10:16:44<322:54:35,  2.20s/it]
  7%|▋         | 42316/569592 [10:16:45<270:25:26,  1.85s/it]
                                                             

  7%|▋         | 42316/569592 [10:16:45<270:25:26,  1.85s/it]
  7%|▋         | 42317/569592 [10:16:46<235:11:29,  1.61s/it]
                                                             

  7%|▋         | 42317/569592 [10:16:46<235:11:29,  1.61s/it]
  7%|▋         | 42318/569592 [10:16:47<206:43:53,  1.41s/it]
                                                             

  7%|▋         | 42318/569592 [10:16:47<206:43:53,  1.41s/it]
  7%|▋         | 42319/569592 [10:16:48<213:17:51,  1.46s/it]
                                                             

  7%|▋         | 42319/569592 [10:16:49<213:17:51,  1.46s/it]
  7%|▋         | 42320/569592 [10:16:53<361:28:02,  2.47s/it]
                                                             

  7%|▋         | 42320/569592 [10:16:53<361:28:02,  2.47s/it]
  7%|▋         | 42321/569592 [10:16:57<400:54:56,  2.74s/it]
                                                             

  7%|▋         | 42321/569592 [10:16:57<400:54:56,  2.74s/it]
  7%|▋         | 42322/569592 [10:17:00<440:54:07,  3.01s/it]
                                                             

  7%|▋         | 42322/569592 [10:17:00<440:54:07,  3.01s/it]
  7%|▋         | 42323/569592 [10:17:01<349:07:42,  2.38s/it]
                                                             

  7%|▋         | 42323/569592 [10:17:01<349:07:42,  2.38s/it]
  7%|▋         | 42324/569592 [10:17:03<327:06:23,  2.23s/it]
                                                             

  7%|▋         | 42324/569592 [10:17:03<327:06:23,  2.23s/it]
  7%|▋         | 42325/569592 [10:17:05<293:56:36,  2.01s/it]
                                                             

  7%|▋         | 42325/569592 [10:17:05<293:56:36,  2.01s/it]
  7%|▋         | 42326/569592 [10:17:07<293:36:00,  2.00s/it]
                                                             

  7%|▋         | 42326/569592 [10:17:07<293:36:00,  2.00s/it]
  7%|▋         | 42327/569592 [10:17:11<384:50:14,  2.63s/it]
                                                             

  7%|▋         | 42327/569592 [10:17:11<384:50:14,  2.63s/it]
  7%|▋         | 42328/569592 [10:17:14<411:17:50,  2.81s/it]
                                                             

  7%|▋         | 42328/569592 [10:17:14<411:17:50,  2.81s/it]
  7%|▋         | 42329/569592 [10:17:15<329:53:46,  2.25s/it]
                                                             

  7%|▋         | 42329/569592 [10:17:15<329:53:46,  2.25s/it]
  7%|▋         | 42330/569592 [10:17:18<379:33:11,  2.59s/it]
                                                             

  7%|▋         | 42330/569592 [10:17:18<379:33:11,  2.59s/it]
  7%|▋         | 42331/569592 [10:17:22<426:31:54,  2.91s/it]
                                                             

  7%|▋         | 42331/569592 [10:17:22<426:31:54,  2.91s/it]
  7%|▋         | 42332/569592 [10:17:26<458:13:41,  3.13s/it]
                                                             

  7%|▋         | 42332/569592 [10:17:26<458:13:41,  3.13s/it]
  7%|▋         | 42333/569592 [10:17:29<468:43:26,  3.20s/it]
                                                             

  7%|▋         | 42333/569592 [10:17:29<468:43:26,  3.20s/it]
  7%|▋         | 42334/569592 [10:17:32<475:09:57,  3.24s/it]
                                                             

  7%|▋         | 42334/569592 [10:17:32<475:09:57,  3.24s/it]
  7%|▋         | 42335/569592 [10:17:36<488:41:03,  3.34s/it]
                                                             

  7%|▋         | 42335/569592 [10:17:36<488:41:03,  3.34s/it]
  7%|▋         | 42336/569592 [10:17:37<383:23:57,  2.62s/it]
                                                             

  7%|▋         | 42336/569592 [10:17:37<383:23:57,  2.62s/it]
  7%|▋         | 42337/569592 [10:17:38<310:02:16,  2.12s/it]
                                                             

  7%|▋         | 42337/569592 [10:17:38<310:02:16,  2.12s/it]
  7%|▋         | 42338/569592 [10:17:39<258:45:09,  1.77s/it]
                                                             

  7%|▋         | 42338/569592 [10:17:39<258:45:09,  1.77s/it]
  7%|▋         | 42339/569592 [10:17:44<405:42:15,  2.77s/it]
                                                             

  7%|▋         | 42339/569592 [10:17:44<405:42:15,  2.77s/it]
  7%|▋         | 42340/569592 [10:17:48<448:21:02,  3.06s/it]
                                                             

  7%|▋         | 42340/569592 [10:17:48<448:21:02,  3.06s/it]
  7%|▋         | 42341/569592 [10:17:51<470:57:09,  3.22s/it]
                                                             

  7%|▋         | 42341/569592 [10:17:51<470:57:09,  3.22s/it]
  7%|▋         | 42342/569592 [10:17:54<470:57:26,  3.22s/it]
                                                             

  7%|▋         | 42342/569592 [10:17:54<470:57:26,  3.22s/it]
  7%|▋         | 42343/569592 [10:17:58<478:00:42,  3.26s/it]
                                                             

  7%|▋         | 42343/569592 [10:17:58<478:00:42,  3.26s/it]
  7%|▋         | 42344/569592 [10:18:01<471:31:09,  3.22s/it]
                                                             

  7%|▋         | 42344/569592 [10:18:01<471:31:09,  3.22s/it]
  7%|▋         | 42345/569592 [10:18:04<472:35:20,  3.23s/it]
                                                             

  7%|▋         | 42345/569592 [10:18:04<472:35:20,  3.23s/it]
  7%|▋         | 42346/569592 [10:18:05<371:08:20,  2.53s/it]
                                                             

  7%|▋         | 42346/569592 [10:18:05<371:08:20,  2.53s/it]
  7%|▋         | 42347/569592 [10:18:08<405:26:16,  2.77s/it]
                                                             

  7%|▋         | 42347/569592 [10:18:08<405:26:16,  2.77s/it]
  7%|▋         | 42348/569592 [10:18:13<498:39:27,  3.40s/it]
                                                             

  7%|▋         | 42348/569592 [10:18:13<498:39:27,  3.40s/it]
  7%|▋         | 42349/569592 [10:18:18<545:03:08,  3.72s/it]
                                                             

  7%|▋         | 42349/569592 [10:18:18<545:03:08,  3.72s/it]
  7%|▋         | 42350/569592 [10:18:21<510:22:41,  3.48s/it]
                                                             

  7%|▋         | 42350/569592 [10:18:21<510:22:41,  3.48s/it]
  7%|▋         | 42351/569592 [10:18:24<496:46:57,  3.39s/it]
                                                             

  7%|▋         | 42351/569592 [10:18:24<496:46:57,  3.39s/it]
  7%|▋         | 42352/569592 [10:18:27<481:11:33,  3.29s/it]
                                                             

  7%|▋         | 42352/569592 [10:18:27<481:11:33,  3.29s/it]
  7%|▋         | 42353/569592 [10:18:30<485:30:28,  3.32s/it]
                                                             

  7%|▋         | 42353/569592 [10:18:30<485:30:28,  3.32s/it]
  7%|▋         | 42354/569592 [10:18:33<480:06:56,  3.28s/it]
                                                             

  7%|▋         | 42354/569592 [10:18:33<480:06:56,  3.28s/it]
  7%|▋         | 42355/569592 [10:18:36<471:47:41,  3.22s/it]
                                                             

  7%|▋         | 42355/569592 [10:18:36<471:47:41,  3.22s/it]
  7%|▋         | 42356/569592 [10:18:40<481:28:23,  3.29s/it]
                                                             

  7%|▋         | 42356/569592 [10:18:40<481:28:23,  3.29s/it]
  7%|▋         | 42357/569592 [10:18:43<484:26:29,  3.31s/it]
                                                             

  7%|▋         | 42357/569592 [10:18:43<484:26:29,  3.31s/it]
  7%|▋         | 42358/569592 [10:18:46<474:51:55,  3.24s/it]
                                                             

  7%|▋         | 42358/569592 [10:18:46<474:51:55,  3.24s/it]
  7%|▋         | 42359/569592 [10:18:50<476:05:31,  3.25s/it]
                                                             

  7%|▋         | 42359/569592 [10:18:50<476:05:31,  3.25s/it]
  7%|▋         | 42360/569592 [10:18:50<372:36:04,  2.54s/it]
                                                             

  7%|▋         | 42360/569592 [10:18:51<372:36:04,  2.54s/it]
  7%|▋         | 42361/569592 [10:18:54<412:30:13,  2.82s/it]
                                                             

  7%|▋         | 42361/569592 [10:18:54<412:30:13,  2.82s/it]
  7%|▋         | 42362/569592 [10:18:57<438:43:52,  3.00s/it]
                                                             

  7%|▋         | 42362/569592 [10:18:57<438:43:52,  3.00s/it]
  7%|▋         | 42363/569592 [10:19:01<459:15:29,  3.14s/it]
                                                             

  7%|▋         | 42363/569592 [10:19:01<459:15:29,  3.14s/it]
  7%|▋         | 42364/569592 [10:19:04<474:30:26,  3.24s/it]
                                                             

  7%|▋         | 42364/569592 [10:19:04<474:30:26,  3.24s/it]
  7%|▋         | 42365/569592 [10:19:08<486:28:52,  3.32s/it]
                                                             

  7%|▋         | 42365/569592 [10:19:08<486:28:52,  3.32s/it]
  7%|▋         | 42366/569592 [10:19:11<493:36:37,  3.37s/it]
                                                             

  7%|▋         | 42366/569592 [10:19:11<493:36:37,  3.37s/it]
  7%|▋         | 42367/569592 [10:19:15<496:38:24,  3.39s/it]
                                                             

  7%|▋         | 42367/569592 [10:19:15<496:38:24,  3.39s/it]
  7%|▋         | 42368/569592 [10:19:16<386:26:59,  2.64s/it]
                                                             

  7%|▋         | 42368/569592 [10:19:16<386:26:59,  2.64s/it]
  7%|▋         | 42369/569592 [10:19:19<430:18:39,  2.94s/it]
                                                             

  7%|▋         | 42369/569592 [10:19:19<430:18:39,  2.94s/it]
  7%|▋         | 42370/569592 [10:19:23<450:06:21,  3.07s/it]
                                                             

  7%|▋         | 42370/569592 [10:19:23<450:06:21,  3.07s/it]
  7%|▋         | 42371/569592 [10:19:26<479:25:54,  3.27s/it]
                                                             

  7%|▋         | 42371/569592 [10:19:26<479:25:54,  3.27s/it]
  7%|▋         | 42372/569592 [10:19:27<376:51:10,  2.57s/it]
                                                             

  7%|▋         | 42372/569592 [10:19:27<376:51:10,  2.57s/it]
  7%|▋         | 42373/569592 [10:19:31<429:45:12,  2.93s/it]
                                                             

  7%|▋         | 42373/569592 [10:19:31<429:45:12,  2.93s/it]
  7%|▋         | 42374/569592 [10:19:35<466:53:40,  3.19s/it]
                                                             

  7%|▋         | 42374/569592 [10:19:35<466:53:40,  3.19s/it]
  7%|▋         | 42375/569592 [10:19:39<508:01:57,  3.47s/it]
                                                             

  7%|▋         | 42375/569592 [10:19:39<508:01:57,  3.47s/it]
  7%|▋         | 42376/569592 [10:19:42<492:30:56,  3.36s/it]
                                                             

  7%|▋         | 42376/569592 [10:19:42<492:30:56,  3.36s/it]
  7%|▋         | 42377/569592 [10:19:45<480:03:34,  3.28s/it]
                                                             

  7%|▋         | 42377/569592 [10:19:45<480:03:34,  3.28s/it]
  7%|▋         | 42378/569592 [10:19:46<376:38:16,  2.57s/it]
                                                             

  7%|▋         | 42378/569592 [10:19:46<376:38:16,  2.57s/it]
  7%|▋         | 42379/569592 [10:19:47<304:17:54,  2.08s/it]
                                                             

  7%|▋         | 42379/569592 [10:19:47<304:17:54,  2.08s/it]
  7%|▋         | 42380/569592 [10:19:48<253:38:50,  1.73s/it]
                                                             

  7%|▋         | 42380/569592 [10:19:48<253:38:50,  1.73s/it]
  7%|▋         | 42381/569592 [10:19:52<370:40:01,  2.53s/it]
                                                             

  7%|▋         | 42381/569592 [10:19:52<370:40:01,  2.53s/it]
  7%|▋         | 42382/569592 [10:19:53<301:19:17,  2.06s/it]
                                                             

  7%|▋         | 42382/569592 [10:19:53<301:19:17,  2.06s/it]
  7%|▋         | 42383/569592 [10:19:57<393:58:37,  2.69s/it]
                                                             

  7%|▋         | 42383/569592 [10:19:58<393:58:37,  2.69s/it]
  7%|▋         | 42384/569592 [10:20:02<468:51:38,  3.20s/it]
                                                             

  7%|▋         | 42384/569592 [10:20:02<468:51:38,  3.20s/it]
  7%|▋         | 42385/569592 [10:20:06<488:42:39,  3.34s/it]
                                                             

  7%|▋         | 42385/569592 [10:20:06<488:42:39,  3.34s/it]
  7%|▋         | 42386/569592 [10:20:06<382:01:13,  2.61s/it]
                                                             

  7%|▋         | 42386/569592 [10:20:06<382:01:13,  2.61s/it]
  7%|▋         | 42387/569592 [10:20:12<490:53:09,  3.35s/it]
                                                             

  7%|▋         | 42387/569592 [10:20:12<490:53:09,  3.35s/it]
  7%|▋         | 42388/569592 [10:20:12<382:45:06,  2.61s/it]
                                                             

  7%|▋         | 42388/569592 [10:20:12<382:45:06,  2.61s/it]
  7%|▋         | 42389/569592 [10:20:16<422:28:38,  2.88s/it]
                                                             

  7%|▋         | 42389/569592 [10:20:16<422:28:38,  2.88s/it]
  7%|▋         | 42390/569592 [10:20:19<441:42:37,  3.02s/it]
                                                             

  7%|▋         | 42390/569592 [10:20:19<441:42:37,  3.02s/it]
  7%|▋         | 42391/569592 [10:20:20<350:15:14,  2.39s/it]
                                                             

  7%|▋         | 42391/569592 [10:20:20<350:15:14,  2.39s/it]
  7%|▋         | 42392/569592 [10:20:21<287:05:06,  1.96s/it]
                                                             

  7%|▋         | 42392/569592 [10:20:21<287:05:06,  1.96s/it]
  7%|▋         | 42393/569592 [10:20:24<347:11:26,  2.37s/it]
                                                             

  7%|▋         | 42393/569592 [10:20:24<347:11:26,  2.37s/it]
  7%|▋         | 42394/569592 [10:20:29<434:20:07,  2.97s/it]
                                                             

  7%|▋         | 42394/569592 [10:20:29<434:20:07,  2.97s/it]
  7%|▋         | 42395/569592 [10:20:32<454:20:25,  3.10s/it]
                                                             

  7%|▋         | 42395/569592 [10:20:32<454:20:25,  3.10s/it]
  7%|▋         | 42396/569592 [10:20:36<472:44:17,  3.23s/it]
                                                             

  7%|▋         | 42396/569592 [10:20:36<472:44:17,  3.23s/it]
  7%|▋         | 42397/569592 [10:20:39<484:27:14,  3.31s/it]
                                                             

  7%|▋         | 42397/569592 [10:20:39<484:27:14,  3.31s/it]
  7%|▋         | 42398/569592 [10:20:42<472:29:00,  3.23s/it]
                                                             

  7%|▋         | 42398/569592 [10:20:42<472:29:00,  3.23s/it]
  7%|▋         | 42399/569592 [10:20:46<485:25:06,  3.31s/it]
                                                             

  7%|▋         | 42399/569592 [10:20:46<485:25:06,  3.31s/it]
  7%|▋         | 42400/569592 [10:20:49<489:43:21,  3.34s/it]
                                                             

  7%|▋         | 42400/569592 [10:20:49<489:43:21,  3.34s/it]
  7%|▋         | 42401/569592 [10:20:53<498:20:00,  3.40s/it]
                                                             

  7%|▋         | 42401/569592 [10:20:53<498:20:00,  3.40s/it]
  7%|▋         | 42402/569592 [10:20:54<388:58:22,  2.66s/it]
                                                             

  7%|▋         | 42402/569592 [10:20:54<388:58:22,  2.66s/it]
  7%|▋         | 42403/569592 [10:20:57<426:33:28,  2.91s/it]
                                                             

  7%|▋         | 42403/569592 [10:20:57<426:33:28,  2.91s/it]
  7%|▋         | 42404/569592 [10:20:58<339:23:42,  2.32s/it]
                                                             

  7%|▋         | 42404/569592 [10:20:58<339:23:42,  2.32s/it]
  7%|▋         | 42405/569592 [10:21:02<397:46:25,  2.72s/it]
                                                             

  7%|▋         | 42405/569592 [10:21:02<397:46:25,  2.72s/it]
  7%|▋         | 42406/569592 [10:21:05<428:19:02,  2.92s/it]
                                                             

  7%|▋         | 42406/569592 [10:21:05<428:19:02,  2.92s/it]
  7%|▋         | 42407/569592 [10:21:06<344:27:43,  2.35s/it]
                                                             

  7%|▋         | 42407/569592 [10:21:06<344:27:43,  2.35s/it]
  7%|▋         | 42408/569592 [10:21:10<413:22:30,  2.82s/it]
                                                             

  7%|▋         | 42408/569592 [10:21:10<413:22:30,  2.82s/it]
  7%|▋         | 42409/569592 [10:21:13<428:39:56,  2.93s/it]
                                                             

  7%|▋         | 42409/569592 [10:21:13<428:39:56,  2.93s/it]
  7%|▋         | 42410/569592 [10:21:14<341:32:57,  2.33s/it]
                                                             

  7%|▋         | 42410/569592 [10:21:14<341:32:57,  2.33s/it]
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  7%|▋         | 424/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
94/569592 [10:25:02<517:41:28,  3.54s/it]
                                                             

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                                           /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (102001683 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                  

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  7%|▋         | 42548/569592 [10:27:27<301:30:19,  2.06s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

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  7%|▋         | 42/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (91462870 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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          /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                   

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  7%|▋         | 42709/569592 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
[10:34:49<489:04:48,  3.34s/it]
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  7%|▋         | 42717/569592 [10:35:10<321:51:32,  2.20s/it]
                                                             

  7%|▋         | 42717/569592 [10:35:10<321:51:32,  2.20s/it]
  7%|▋         | 42718/569592 [10:35:13<388:04:34,  2.65s/it]
                                                             

  7%|▋         | 42718/569592 [10:35:13<388:04:34,  2.65s/it]
  7%|▋         | 42719/569592 [10:35:18<464:14:02,  3.17s/it]
                                                             

  7%|▋         | 42719/569592 [10:35:18<464:14:02,  3.17s/it]
  8%|▊         | 42720/569592 [10:35:19<375:11:39,  2.56s/it]
                                                             

  8%|▊         | 42720/569592 [10:35:19<375:11:39,  2.56s/it]
  8%|▊         | 42721/569592 [10:35:20<303:12:39,  2.07s/it]
                                                             

  8%|▊         | 42721/569592 [10:35:20<303:12:39,  2.07s/it]
  8%|▊         | 42722/569592 [10:35:23<361:07:43,  2.47s/it]
                                                             

  8%|▊         | 42722/569592 [10:35:23<361:07:43,  2.47s/it]
  8%|▊         | 42723/569592 [10:35:28<460:16:59,  3.15s/it]
                                                             

  8%|▊         | 42723/569592 [10:35:28<460:16:59,  3.15s/it]
  8%|▊         | 42724/569592 [10:35:31<471:44:49,  3.22s/it]
                                                             

  8%|▊         | 42724/569592 [10:35:31<471:44:49,  3.22s/it]
  8%|▊         | 42725/569592 [10:35:32<370:07:15,  2.53s/it]
                                                             

  8%|▊         | 42725/569592 [10:35:32<370:07:15,  2.53s/it]
  8%|▊         | 42726/569592 [10:35:36<423:31:41,  2.89s/it]
                                                             

  8%|▊         | 42726/569592 [10:35:36<423:31:41,  2.89s/it]
  8%|▊         | 42727/569592 [10:35:39<438:56:13,  3.00s/it]
                                                             

  8%|▊         | 42727/569592 [10:35:39<438:56:13,  3.00s/it]
  8%|▊         | 42728/569592 [10:35:43<458:56:51,  3.14s/it]
                                                             

  8%|▊         | 42728/569592 [10:35:43<458:56:51,  3.14s/it]
  8%|▊         | 42729/569592 [10:35:44<361:43:56,  2.47s/it]
                                                             

  8%|▊         | 42729/569592 [10:35:44<361:43:56,  2.47s/it]
  8%|▊         | 42730/569592 [10:35:47<426:42:36,  2.92s/it]
                                                             

  8%|▊         | 42730/569592 [10:35:47<426:42:36,  2.92s/it]
  8%|▊         | 42731/569592 [10:35:48<339:17:22,  2.32s/it]
                                                             

  8%|▊         | 42731/569592 [10:35:48<339:17:22,  2.32s/it]
  8%|▊         | 42732/569592 [10:35:53<424:21:13,  2.90s/it]
                                                             

  8%|▊         | 42732/569592 [10:35:53<424:21:13,  2.90s/it]
  8%|▊         | 42733/569592 [10:35:56<433:00:46,  2.96s/it]
                                                             

  8%|▊         | 42733/569592 [10:35:56<433:00:46,  2.96s/it]
  8%|▊         | 42734/569592 [10:35:57<344:55:14,  2.36s/it]
                                                             

  8%|▊         | 42734/569592 [10:35:57<344:55:14,  2.36s/it]
  8%|▊         | 42735/569592 [10:36:00<399:29:46,  2.73s/it]
                                                             

  8%|▊         | 42735/569592 [10:36:00<399:29:46,  2.73s/it]
  8%|▊         | 42736/569592 [10:36:04<450:06:58,  3.08s/it]
                                                             

  8%|▊         | 42736/569592 [10:36:04<450:06:58,  3.08s/it]
  8%|▊         | 42737/569592 [10:36:07<458:21:56,  3.13s/it]
                                                             

  8%|▊         | 42737/569592 [10:36:07<458:21:56,  3.13s/it]
  8%|▊         | 42738/569592 [10:36:11<464:11:26,  3.17s/it]
                                                             

  8%|▊         | 42738/569592 [10:36:11<464:11:26,  3.17s/it]
  8%|▊         | 42739/569592 [10:36:14<483:23:26,  3.30s/it]
                                                             

  8%|▊         | 42739/569592 [10:36:14<483:23:26,  3.30s/it]
  8%|▊         | 42740/569592 [10:36:15<378:27:12,  2.59s/it]
                                                             

  8%|▊         | 42740/569592 [10:36:15<378:27:12,  2.59s/it]
  8%|▊         | 42741/569592 [10:36:16<309:34:12,  2.12s/it]
                                                             

  8%|▊         | 42741/569592 [10:36:16<309:34:12,  2.12s/it]
  8%|▊         | 42742/569592 [10:36:17<260:13:43,  1.78s/it]
                                                             

  8%|▊         | 42742/569592 [10:36:17<260:13:43,  1.78s/it]
  8%|▊         | 42743/569592 [10:36:21<341:58:03,  2.34s/it]
                                                             

  8%|▊         | 42743/569592 [10:36:21<341:58:03,  2.34s/it]
  8%|▊         | 42744/569592 [10:36:25<405:02:53,  2.77s/it]
                                                             

  8%|▊         | 42744/569592 [10:36:25<405:02:53,  2.77s/it]
  8%|▊         | 42745/569592 [10:36:28<435:22:13,  2.97s/it]
                                                             

  8%|▊         | 42745/569592 [10:36:28<435:22:13,  2.97s/it]
  8%|▊         | 42746/569592 [10:36:31<451:51:16,  3.09s/it]
                                                             

  8%|▊         | 42746/569592 [10:36:31<451:51:16,  3.09s/it]
  8%|▊         | 42747/569592 [10:36:35<486:09:30,  3.32s/it]
                                                             

  8%|▊         | 42747/569592 [10:36:35<486:09:30,  3.32s/it]
  8%|▊         | 42748/569592 [10:36:36<381:19:45,  2.61s/it]
                                                             

  8%|▊         | 42748/569592 [10:36:36<381:19:45,  2.61s/it]
  8%|▊         | 42749/569592 [10:36:40<416:37:06,  2.85s/it]
                                                             

  8%|▊         | 42749/569592 [10:36:40<416:37:06,  2.85s/it]
  8%|▊         | 42750/569592 [10:36:43<452:54:52,  3.09s/it]
                                                             

  8%|▊         | 42750/569592 [10:36:43<452:54:52,  3.09s/it]
  8%|▊         | 42751/569592 [10:36:47<477:34:29,  3.26s/it]
                                                             

  8%|▊         | 42751/569592 [10:36:47<477:34:29,  3.26s/it]
  8%|▊         | 42752/569592 [10:36:50<473:34:38,  3.24s/it]
                                                             

  8%|▊         | 42752/569592 [10:36:50<473:34:38,  3.24s/it]
  8%|▊         | 42753/569592 [10:36:54<485:55:07,  3.32s/it]
                                                             

  8%|▊         | 42753/569592 [10:36:54<485:55:07,  3.32s/it]
  8%|▊         | 42754/569592 [10:36:59<551:11:21,  3.77s/it]
                                                             

  8%|▊         | 42754/569592 [10:36:59<551:11:21,  3.77s/it]
  8%|▊         | 42755/569592 [10:37:02<519:12:04,  3.55s/it]
                                                             

  8%|▊         | 42755/569592 [10:37:02<519:12:04,  3.55s/it]
  8%|▊         | 42756/569592 [10:37:02<403:04:12,  2.75s/it]
                                                             

  8%|▊         | 42756/569592 [10:37:02<403:04:12,  2.75s/it]
  8%|▊         | 42757/569592 [10:37:03<322:51:38,  2.21s/it]
                                                             

  8%|▊         | 42757/569592 [10:37:03<322:51:38,  2.21s/it]
  8%|▊         | 42758/569592 [10:37:07<380:21:51,  2.60s/it]
                                                             

  8%|▊         | 42758/569592 [10:37:07<380:21:51,  2.60s/it]
  8%|▊         | 42759/569592 [10:37:11<439:28:19,  3.00s/it]
                                                             

  8%|▊         | 42759/569592 [10:37:11<439:28:19,  3.00s/it]
  8%|▊         | 42760/569592 [10:37:12<350:06:03,  2.39s/it]
                                                             

  8%|▊         | 42760/569592 [10:37:12<350:06:03,  2.39s/it]
  8%|▊         | 42761/569592 [10:37:16<410:20:15,  2.80s/it]
                                                             

  8%|▊         | 42761/569592 [10:37:16<410:20:15,  2.80s/it]
  8%|▊         | 42762/569592 [10:37:19<426:01:30,  2.91s/it]
                                                             

  8%|▊         | 42762/569592 [10:37:19<426:01:30,  2.91s/it]
  8%|▊         | 42763/569592 [10:37:23<470:47:10,  3.22s/it]
                                                             

  8%|▊         | 42763/569592 [10:37:23<470:47:10,  3.22s/it]
  8%|▊         | 42764/569592 [10:37:26<478:55:53,  3.27s/it]
                                                             

  8%|▊         | 42764/569592 [10:37:26<478:55:53,  3.27s/it]
  8%|▊         | 42765/569592 [10:37:29<468:17:03,  3.20s/it]
                                                             

  8%|▊         | 42765/569592 [10:37:29<468:17:03,  3.20s/it]
  8%|▊         | 42766/569592 [10:37:32<473:18:06,  3.23s/it]
                                                             

  8%|▊         | 42766/569592 [10:37:32<473:18:06,  3.23s/it]
  8%|▊         | 42767/569592 [10:37:36<480:59:22,  3.29s/it]
                                                             

  8%|▊         | 42767/569592 [10:37:36<480:59:22,  3.29s/it]
  8%|▊         | 42768/569592 [10:37:37<376:33:26,  2.57s/it]
                                                             

  8%|▊         | 42768/569592 [10:37:37<376:33:26,  2.57s/it]
  8%|▊         | 42769/569592 [10:37:38<305:14:06,  2.09s/it]
                                                             

  8%|▊         | 42769/569592 [10:37:38<305:14:06,  2.09s/it]
  8%|▊         | 42770/569592 [10:37:41<367:40:26,  2.51s/it]
                                                             

  8%|▊         | 42770/569592 [10:37:41<367:40:26,  2.51s/it]
  8%|▊         | 42771/569592 [10:37:42<300:16:17,  2.05s/it]
                                                             

  8%|▊         | 42771/569592 [10:37:42<300:16:17,  2.05s/it]
  8%|▊         | 42772/569592 [10:37:46<360:56:21,  2.47s/it]
                                                             

  8%|▊         | 42772/569592 [10:37:46<360:56:21,  2.47s/it]
  8%|▊         | 42773/569592 [10:37:47<294:47:48,  2.01s/it]
                                                             

  8%|▊         | 42773/569592 [10:37:47<294:47:48,  2.01s/it]
  8%|▊         | 42774/569592 [10:37:48<248:53:47,  1.70s/it]
                                                             

  8%|▊         | 42774/569592 [10:37:48<248:53:47,  1.70s/it]
  8%|▊         | 42775/569592 [10:37:51<324:05:59,  2.21s/it]
                                                             

  8%|▊         | 42775/569592 [10:37:51<324:05:59,  2.21s/it]
  8%|▊         | 42776/569592 [10:37:54<376:00:12,  2.57s/it]
                                                             

  8%|▊         | 42776/569592 [10:37:54<376:00:12,  2.57s/it]
  8%|▊         | 42777/569592 [10:37:55<306:39:42,  2.10s/it]
                                                             

  8%|▊         | 42777/569592 [10:37:55<306:39:42,  2.10s/it]
  8%|▊         | 42778/569592 [10:37:59<381:55:26,  2.61s/it]
                                                             

  8%|▊         | 42778/569592 [10:37:59<381:55:26,  2.61s/it]
  8%|▊         | 42779/569592 [10:38:00<310:08:05,  2.12s/it]
                                                             

  8%|▊         | 42779/569592 [10:38:00<310:08:05,  2.12s/it]
  8%|▊         | 42780/569592 [10:38:01<262:46:00,  1.80s/it]
                                                             

  8%|▊         | 42780/569592 [10:38:01<262:46:00,  1.80s/it]
  8%|▊         | 42781/569592 [10:38:05<336:19:38,  2.30s/it]
                                                             

  8%|▊         | 42781/569592 [10:38:05<336:19:38,  2.30s/it]
  8%|▊         | 42782/569592 [10:38:08<377:56:32,  2.58s/it]
                                                             

  8%|▊         | 42782/569592 [10:38:08<377:56:32,  2.58s/it]
  8%|▊         | 42783/569592 [10:38:09<305:23:50,  2.09s/it]
                                                             

  8%|▊         | 42783/569592 [10:38:09<305:23:50,  2.09s/it]
  8%|▊         | 42784/569592 [10:38:10<288:27:53,  1.97s/it]
                                                             

  8%|▊         | 42784/569592 [10:38:11<288:27:53,  1.97s/it]
  8%|▊         | 42785/569592 [10:38:14<351:48:30,  2.40s/it]
                                                             

  8%|▊         | 42785/569592 [10:38:14<351:48:30,  2.40s/it]
  8%|▊         | 42786/569592 [10:38:17<389:26:08,  2.66s/it]
                                                             

  8%|▊         | 42786/569592 [10:38:17<389:26:08,  2.66s/it]
  8%|▊         | 42787/569592 [10:38:18<313:51:18,  2.14s/it]
                                                             

  8%|▊         | 42787/569592 [10:38:18<313:51:18,  2.14s/it]
  8%|▊         | 42788/569592 [10:38:21<339:23:20,  2.32s/it]
                                                             

  8%|▊         | 42788/569592 [10:38:21<339:23:20,  2.32s/it]
  8%|▊         | 42789/569592 [10:38:22<278:16:35,  1.90s/it]
                                                             

  8%|▊         | 42789/569592 [10:38:22<278:16:35,  1.90s/it]
  8%|▊         | 42790/569592 [10:38:26<369:30:35,  2.53s/it]
                                                             

  8%|▊         | 42790/569592 [10:38:26<369:30:35,  2.53s/it]
  8%|▊         | 42791/569592 [10:38:30<432:01:45,  2.95s/it]
                                                             

  8%|▊         | 42791/569592 [10:38:30<432:01:45,  2.95s/it]
  8%|▊         | 42792/569592 [10:38:34<478:00:36,  3.27s/it]
                                                             

  8%|▊         | 42792/569592 [10:38:34<478:00:36,  3.27s/it]
  8%|▊         | 42793/569592 [10:38:37<496:14:09,  3.39s/it]
                                                             

  8%|▊         | 42793/569592 [10:38:37<496:14:09,  3.39s/it]
  8%|▊         | 42794/569592 [10:38:38<389:02:32,  2.66s/it]
                                                             

  8%|▊         | 42794/569592 [10:38:38<389:02:32,  2.66s/it]
  8%|▊         | 42795/569592 [10:38:39<313:41:22,  2.14s/it]
                                                             

  8%|▊         | 42795/569592 [10:38:39<313:41:22,  2.14s/it]
  8%|▊         | 42796/569592 [10:38:43<371:18:20,  2.54s/it]
                                                             

  8%|▊         | 42796/569592 [10:38:43<371:18:20,  2.54s/it]
  8%|▊         | 42797/569592 [10:38:44<300:41:24,  2.05s/it]
                                                             

  8%|▊         | 42797/569592 [10:38:44<300:41:24,  2.05s/it]
  8%|▊         | 42798/569592 [10:38:47<359:43:01,  2.46s/it]
                                                             

  8%|▊         | 42798/569592 [10:38:47<359:43:01,  2.46s/it]
  8%|▊         | 42799/569592 [10:38:48<293:17:29,  2.00s/it]
                                                             

  8%|▊         | 42799/569592 [10:38:48<293:17:29,  2.00s/it]
  8%|▊         | 42800/569592 [10:38:52<381:30:41,  2.61s/it]
                                                             

  8%|▊         | 42800/569592 [10:38:52<381:30:41,  2.61s/it]
  8%|▊         | 42801/569592 [10:38:55<409:50:11,  2.80s/it]
                                                             

  8%|▊         | 42801/569592 [10:38:55<409:50:11,  2.80s/it]
  8%|▊         | 42802/569592 [10:38:57<341:52:11,  2.34s/it]
                                                             

  8%|▊         | 42802/569592 [10:38:57<341:52:11,  2.34s/it]
  8%|▊         | 42803/569592 [10:38:59<343:33:20,  2.35s/it]
                                                             

  8%|▊         | 42803/569592 [10:38:59<343:33:20,  2.35s/it]
  8%|▊         | 42804/569592 [10:39:02<387:46:20,  2.65s/it]
                                                             

  8%|▊         | 42804/569592 [10:39:02<387:46:20,  2.65s/it]
  8%|▊         | 42805/569592 [10:39:06<416:33:09,  2.85s/it]
                                                             

  8%|▊         | 42805/569592 [10:39:06<416:33:09,  2.85s/it]
  8%|▊         | 42806/569592 [10:39:10<500:55:09,  3.42s/it]
                                                             

  8%|▊         | 42806/569592 [10:39:10<500:55:09,  3.42s/it]
  8%|▊         | 42807/569592 [10:39:14<517:15:13,  3.53s/it]
                                                             

  8%|▊         | 42807/569592 [10:39:14<517:15:13,  3.53s/it]
  8%|▊         | 42808/569592 [10:39:15<401:46:45,  2.75s/it]
                                                             

  8%|▊         | 42808/569592 [10:39:15<401:46:45,  2.75s/it]
  8%|▊         | 42809/569592 [10:39:19<434:00:11,  2.97s/it]
                                                             

  8%|▊         | 42809/569592 [10:39:19<434:00:11,  2.97s/it]
  8%|▊         | 42810/569592 [10:39:22<475:48:11,  3.25s/it]
                                                             

  8%|▊         | 42810/569592 [10:39:22<475:48:11,  3.25s/it]
  8%|▊         | 42811/569592 [10:39:27<515:39:25,  3.52s/it]
                                                             

  8%|▊         | 42811/569592 [10:39:27<515:39:25,  3.52s/it]
  8%|▊         | 42812/569592 [10:39:32<601:18:00,  4.11s/it]
                                                             

  8%|▊         | 42812/569592 [10:39:32<601:18:00,  4.11s/it]
  8%|▊         | 42813/569592 [10:39:33<463:33:21,  3.17s/it]
                                                             

  8%|▊         | 42813/569592 [10:39:33<463:33:21,  3.17s/it]
  8%|▊         | 42814/569592 [10:39:37<491:29:36,  3.36s/it]
                                                             

  8%|▊         | 42814/569592 [10:39:37<491:29:36,  3.36s/it]
  8%|▊         | 42815/569592 [10:39:41<507:30:30,  3.47s/it]
                                                             

  8%|▊         | 42815/569592 [10:39:41<507:30:30,  3.47s/it]
  8%|▊         | 42816/569592 [10:39:44<490:51:30,  3.35s/it]
                                                             

  8%|▊         | 42816/569592 [10:39:44<490:51:30,  3.35s/it]
  8%|▊         | 42817/569592 [10:39:45<383:49:25,  2.62s/it]
                                                             

  8%|▊         | 42817/569592 [10:39:45<383:49:25,  2.62s/it]
  8%|▊         | 42818/569592 [10:39:48<414:03:08,  2.83s/it]
                                                             

  8%|▊         | 42818/569592 [10:39:48<414:03:08,  2.83s/it]
  8%|▊         | 42819/569592 [10:39:49<334:51:01,  2.29s/it]
                                                             

  8%|▊         | 42819/569592 [10:39:49<334:51:01,  2.29s/it]
  8%|▊         | 42820/569592 [10:39:53<403:46:44,  2.76s/it]
                                                             

  8%|▊         | 42820/569592 [10:39:53<403:46:44,  2.76s/it]
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                /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (96154916 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                             

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  8%|▊         | 42859/569592 [10:41:44<407:43:10,  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (94586400 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
2.79s/it]
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                                                           /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95699712 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
  

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  8%|▊         | 43000/569592 [10:48:19<413:36:00,  2.83s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-43000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-43000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-43000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-43000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-43000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-43000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-42000] due to args.save_total_limit

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  8%|�/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (97712010 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  8%|▊     /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115411512 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
    | 43226/569592 [11:00:50<306:18:31,  2.09s/it]
                                                             

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                                  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (108234795 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                           

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                        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                     

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  warnings.warn(
,  3.35s/it]
                                                             

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  8%|▊         | 43440/569592 [11:10:35<460:42:37,  3.15s/it]
                                                             

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  8%|▊         | 43442/569592 [11:10:42<478:38:50,  3.27s/it]
                                                             

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  8%|▊         | 43445/569592 [11:10:50<419:47:48,  2.87s/it]
                                                             

  8%|▊         | 43445/569592 [11:10:50<419:47:48,  2.87s/it]
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  8%|▊         | 43446/569592 [11:10:54<461:58:29,  3.16s/it]
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  8%|▊         | 43449/569592 [11:11:02<449:52:41,  3.08s/it]
                                                             

  8%|▊         | 43449/569592 [11:11:02<449:52:41,  3.08s/it]
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  8%|▊         | 43451/569592 [11:11:09<475:40:10,  3.25s/it]
                                                             

  8%|▊         | 43451/569592 [11:11:09<475:40:10,  3.25s/it]
  8%|▊         | 43452/569592 [11:11:10<373:33:09,  2.56s/it]
                                                             

  8%|▊         | 43452/569592 [11:11:10<373:33:09,  2.56s/it]
  8%|▊         | 43453/569592 [11:11:11<302:45:25,  2.07s/it]
                                                             

  8%|▊         | 43453/569592 [11:11:11<302:45:25,  2.07s/it]
  8%|▊         | 43454/569592 [11:11:12<253:10:05,  1.73s/it]
                                                             

  8%|▊         | 43454/569592 [11:11:12<253:10:05,  1.73s/it]
  8%|▊         | 43455/569592 [11:11:16<335:35:21,  2.30s/it]
                                                             

  8%|▊         | 43455/569592 [11:11:16<335:35:21,  2.30s/it]
  8%|▊         | 43456/569592 [11:11:16<276:14:08,  1.89s/it]
                                                             

  8%|▊         | 43456/569592 [11:11:16<276:14:08,  1.89s/it]
  8%|▊         | 43457/569592 [11:11:17<234:14:15,  1.60s/it]
                                                             

  8%|▊         | 43457/569592 [11:11:17<234:14:15,  1.60s/it]
  8%|▊         | 43458/569592 [11:11:18<204:31:48,  1.40s/it]
                                                             

  8%|▊         | 43458/569592 [11:11:18<204:31:48,  1.40s/it]
  8%|▊         | 43459/569592 [11:11:19<184:49:30,  1.26s/it]
                                                             

  8%|▊         | 43459/569592 [11:11:19<184:49:30,  1.26s/it]
  8%|▊         | 43460/569592 [11:11:23<311:42:22,  2.13s/it]
                                                             

  8%|▊         | 43460/569592 [11:11:23<311:42:22,  2.13s/it]
  8%|▊         | 43461/569592 [11:11:24<259:59:34,  1.78s/it]
                                                             

  8%|▊         | 43461/569592 [11:11:24<259:59:34,  1.78s/it]
  8%|▊         | 43462/569592 [11:11:28<330:46:43,  2.26s/it]
                                                             

  8%|▊         | 43462/569592 [11:11:28<330:46:43,  2.26s/it]
  8%|▊         | 43463/569592 [11:11:32<407:27:45,  2.79s/it]
                                                             

  8%|▊         | 43463/569592 [11:11:32<407:27:45,  2.79s/it]
  8%|▊         | 43464/569592 [11:11:37<506:37:14,  3.47s/it]
                                                             

  8%|▊         | 43464/569592 [11:11:37<506:37:14,  3.47s/it]
  8%|▊         | 43465/569592 [11:11:40<512:10:52,  3.50s/it]
                                                             

  8%|▊         | 43465/569592 [11:11:40<512:10:52,  3.50s/it]
  8%|▊         | 43466/569592 [11:11:44<530:00:47,  3.63s/it]
                                                             

  8%|▊         | 43466/569592 [11:11:44<530:00:47,  3.63s/it]
  8%|▊         | 43467/569592 [11:11:48<539:06:43,  3.69s/it]
                                                             

  8%|▊         | 43467/569592 [11:11:48<539:06:43,  3.69s/it]
  8%|▊         | 43468/569592 [11:11:51<511:27:44,  3.50s/it]
                                                             

  8%|▊         | 43468/569592 [11:11:52<511:27:44,  3.50s/it]
  8%|▊         | 43469/569592 [11:11:52<413:36:49,  2.83s/it]
                                                             

  8%|▊         | 43469/569592 [11:11:53<413:36:49,  2.83s/it]
  8%|▊         | 43470/569592 [11:11:56<436:12:34,  2.98s/it]
                                                             

  8%|▊         | 43470/569592 [11:11:56<436:12:34,  2.98s/it]
  8%|▊         | 43471/569592 [11:11:59<458:06:02,  3.13s/it]
                                                             

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  8%|▊         | 43472/569592 [11:12:03<490:56:30,  3.36s/it]
                                                             

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  8%|▊         | 43473/569592 [11:12:06<480:43:27,  3.29s/it]
                                                             

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  8%|▊         | 43474/569592 [11:12:09<473:25:27,  3.24s/it]
                                                             

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  8%|▊         | 43475/569592 [11:12:10<371:38:14,  2.54s/it]
                                                             

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  8%|▊         | 43476/569592 [11:12:14<402:40:19,  2.76s/it]
                                                             

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  8%|▊         | 43477/569592 [11:12:15<324:27:05,  2.22s/it]
                                                             

  8%|▊         | 43477/569592 [11:12:15<324:27:05,  2.22s/it]
  8%|▊         | 43478/569592 [11:12:19<416:29:34,  2.85s/it]
                                                             

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  8%|▊         | 43479/569592 [11:12:20<334:57:41,  2.29s/it]
                                                             

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  8%|▊         | 43480/569592 [11:12:23<380:30:47,  2.60s/it]
                                                             

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  8%|▊         | 43500/569592 [11:13:07<241:43:41,  1.65s/it]
  8%|▊         | 43501/569592 [11:13:10<314:35:07,  2.15s/it]
                                                             

  8%|▊         | 43501/569592 [11:13:10<314:35:07,  2.15s/it]
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  8%|▊         | 43502/569592 [11:13:13<370:20:22,  2.53s/it]
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  8%|▊         | 43507/569592 [11:13:30<440:33:03,  3.01s/it]
                                                             

  8%|▊         | 43507/569592 [11:13:30<440:33:03,  3.01s/it]
  8%|▊         | 43508/569592 [11:13:35<526:17:57,  3.60s/it]
                                                             

  8%|▊         | 43508/569592 [11:13:35<526:17:57,  3.60s/it]
  8%|▊         | 43509/569592 [11:13:36<407:20:55,  2.79s/it]
                                                             

  8%|▊         | 43509/569592 [11:13:36<407:20:55,  2.79s/it]
  8%|▊         | 43510/569592 [11:13:39/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
<444:31:53,  3.04s/it]
                                                             

  8%|▊         | 43510/569592 [11:13:39<444:31:53,  3.04s/it]
  8%|▊         | 43511/569592 [11:13:43<452:18:03,  3.10s/it]
                                                             

  8%|▊         | 43511/569592 [11:13:43<452:18:03,  3.10s/it]
  8%|▊         | 43512/569592 [11:13:46<462:56:16,  3.17s/it]
                                                             

  8%|▊         | 43512/569592 [11:13:46<462:56:16,  3.17s/it]
  8%|▊         | 43513/569592 [11:13:50<508:36:36,  3.48s/it]
                                                             

  8%|▊         | 43513/569592 [11:13:50<508:36:36,  3.48s/it]
  8%|▊         | 43514/569592 [11:13:53<495:01:53,  3.39s/it]
                                                             

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  8%|▊         | 43515/569592 [11:13:57<512:21:04,  3.51s/it]
                                                             

  8%|▊         | 43515/569592 [11:13:57<512:21:04,  3.51s/it]
  8%|▊         | 43516/569592 [11:14:01<533:00:48,  3.65s/it]
                                                             

  8%|▊         | 43516/569592 [11:14:01<533:00:48,  3.65s/it]
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  8%|▊         | 43518/569592 [11:14:09<563:14:16,  3.85s/it]
                                                             

  8%|▊         | 43518/569592 [11:14:09<563:14:16,  3.85s/it]
  8%|▊         | 43519/569592 [11:14:12<533:14:57,  3.65s/it]
                                                             

  8%|▊         | 43519/569592 [11:14:12<533:14:57,  3.65s/it]
  8%|▊         | 43520/569592 [11:14:17<568:15:03,  3.89s/it]
                                                             

  8%|▊         | 43520/569592 [11:14:17<568:15:03,  3.89s/it]
  8%|▊         | 43521/569592 [11:14:20<558:54:16,  3.82s/it]
                                                             

  8%|▊         | 43521/569592 [11:14:20<558:54:16,  3.82s/it]
  8%|▊         | 43522/569592 [11:14:21<429:05:34,  2.94s/it]
                                                             

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  8%|▊         | 43523/569592 [11:14:25<448:16:24,  3.07s/it]
                                                             

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  8%|▊         | 43524/569592 [11:14:28<475:16:44,  3.25s/it]
                                                             

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  8%|▊         | 43525/569592 [11:14:32<479:01:18,  3.28s/it]
                                                             

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  8%|▊         | 43526/569592 [11:14:35<469:15:41,  3.21s/it]
                                                             

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  8%|▊         | 43532/569592 [11:14:52<482:11:43,  3.30s/it]
                                                             

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  8%|▊         | 43533/569592 [11:14:53<377:30:40,  2.58s/it]
                                                             

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  8%|▊         | 43534/569592 [11:14:56<419:36:36,  2.87s/it]
                                                             

  8%|▊         | 43534/569592 [11:14:56<419:36:36,  2.87s/it]
  8%|▊         | 43535/569592 [11:14:57<336:29:31,  2.30s/it]
                                                             

  8%|▊         | 43535/569592 [11:14:57<336:29:31,  2.30s/it]
  8%|▊         | 43536/569592 [11:15:01<399:16:46,  2.73s/it]
                                                             

  8%|▊         | 43536/569592 [11:15:01<399:16:46,  2.73s/it]
  8%|▊         | 43537/569592 [11:15:04<433:13:54,  2.96s/it]
                                                             

  8%|▊         | 43537/569592 [11:15:04<433:13:54,  2.96s/it]
  8%|▊         | 43538/569592 [11:15:08<469:54:33,  3.22s/it]
                                                             

  8%|▊         | 43538/569592 [11:15:08<469:54:33,  3.22s/it]
  8%|▊         | 43539/569592 [11:15:11<471:38:05,  3.23s/it]
                                                             

  8%|▊         | 43539/569592 [11:15:11<471:38:05,  3.23s/it]
  8%|▊         | 43540/569592 [11:15:15<481:04:55,  3.29s/it]
                                                             

  8%|▊         | 43540/569592 [11:15:15<481:04:55,  3.29s/it]
  8%|▊         | 43541/569592 [11:15:18<475:07:50,  3.25s/it]
                                                             

  8%|▊         | 43541/569592 [11:15:18<475:07:50,  3.25s/it]
  8%|▊         | 43542/569592 [11:15:21<467:32:44,  3.20s/it]
                                                             

  8%|▊         | 43542/569592 [11:15:21<467:32:44,  3.20s/it]
  8%|▊         | 43543/569592 [11:15:24<463:45:54,  3.17s/it]
                                                             

  8%|▊         | 43543/569592 [11:15:24<463:45:54,  3.17s/it]
  8%|▊         | 43544/569592 [11:15:28<476:10:24,  3.26s/it]
                                                             

  8%|▊         | 43544/569592 [11:15:28<476:10:24,  3.26s/it]
  8%|▊         | 43545/569592 [11:15:29<373:44:12,  2.56s/it]
                                                             

  8%|▊         | 43545/569592 [11:15:29<373:44:12,  2.56s/it]
  8%|▊         | 43546/569592 [11:15:32<426:36:23,  2.92s/it]
                                                             

  8%|▊         | 43546/569592 [11:15:32<426:36:23,  2.92s/it]
  8%|▊         | 43547/569592 [11:15:37<525:36:40,  3.60s/it]
                                                             

  8%|▊         | 43547/569592 [11:15:38<525:36:40,  3.60s/it]
  8%|▊         | 43548/569592 [11:15:41<516:15:22,  3.53s/it]
                                                             

  8%|▊         | 43548/569592 [11:15:41<516:15:22,  3.53s/it]
  8%|▊         | 43549/569592 [11:15:42<400:45:10,  2.74s/it]
                                                             

  8%|▊         | 43549/569592 [11:15:42<400:45:10,  2.74s/it]
  8%|▊         | 43550/569592 [11:15:43<322:40:27,  2.21s/it]
                                                             

  8%|▊         | 43550/569592 [11:15:43<322:40:27,  2.21s/it]
  8%|▊         | 43551/569592 [11:15:44<269:06:12,  1.84s/it]
                                                             

  8%|▊         | 43551/569592 [11:15:44<269:06:12,  1.84s/it]
  8%|▊         | 43552/569592 [11:15:48<368:06:13,  2.52s/it]
                                                             

  8%|▊         | 43552/569592 [11:15:48<368:06:13,  2.52s/it]
  8%|▊         | 43553/569592 [11:15:49<300:20:41,  2.06s/it]
                                                             

  8%|▊         | 43553/569592 [11:15:49<300:20:41,  2.06s/it]
  8%|▊         | 43554/569592 [11:15:50<250:41:23,  1.72s/it]
                                                             

  8%|▊         | 43554/569592 [11:15:50<250:41:23,  1.72s/it]
  8%|▊         | 43555/569592 [11:15:54<345:19:10,  2.36s/it]
                                                             

  8%|▊         | 43555/569592 [11:15:54<345:19:10,  2.36s/it]
  8%|▊         | 43556/569592 [11:15:55<283:26:10,  1.94s/it]
                                                             

  8%|▊         | 43556/569592 [11:15:55<283:26:10,  1.94s/it]
  8%|▊         | 43557/569592 [11:15:58<368:12:39,  2.52s/it]
                                                             

  8%|▊         | 43557/569592 [11:15:58<368:12:39,  2.52s/it]
  8%|▊         | 43558/569592 [11:16:02<404:51:50,  2.77s/it]
                                                             

  8%|▊         | 43558/569592 [11:16:02<404:51:50,  2.77s/it]
  8%|▊         | 43559/569592 [11:16:05<444:56:45,  3.05s/it]
                                                             

  8%|▊         | 43559/569592 [11:16:05<444:56:45,  3.05s/it]
  8%|▊         | 43560/569592 [11:16:09<474:15:43,  3.25s/it]
                                                             

  8%|▊         | 43560/569592 [11:16:09<474:15:43,  3.25s/it]
  8%|▊         | 43561/569592 [11:16:13<485:46:01,  3.32s/it]
                                                             

  8%|▊         | 43561/569592 [11:16:13<485:46:01,  3.32s/it]
  8%|▊         | 43562/569592 [11:16:14<380:18:21,  2.60s/it]
                                                             

  8%|▊         | 43562/569592 [11:16:14<380:18:21,  2.60s/it]
  8%|▊         | 43563/569592 [11:16:15<307:50:03,  2.11s/it]
                                                             

  8%|▊         | 43563/569592 [11:16:15<307:50:03,  2.11s/it]
  8%|▊         | 43564/569592 [11:16:18<371:33:13,  2.54s/it]
                                                             

  8%|▊         | 43564/569592 [11:16:18<371:33:13,  2.54s/it]
  8%|▊         | 43565/569592 [11:16:23<459:26:45,  3.14s/it]
                                                             

  8%|▊         | 43565/569592 [11:16:23<459:26:45,  3.14s/it]
  8%|▊         | 43566/569592 [11:16:26<470:57:56,  3.22s/it]
                                                             

  8%|▊         | 43566/569592 [11:16:26<470:57:56,  3.22s/it]
  8%|▊         | 43567/569592 [11:16:27<369:52:35,  2.53s/it]
                                                             

  8%|▊         | 43567/569592 [11:16:27<369:52:35,  2.53s/it]
  8%|▊         | 43568/569592 [11:16:30<398:27:11,  2.73s/it]
                                                             

  8%|▊         | 43568/569592 [11:16:30<398:27:11,  2.73s/it]
  8%|▊         | 43569/569592 [11:16:34<440:48:24,  3.02s/it]
                                                             

  8%|▊         | 43569/569592 [11:16:34<440:48:24,  3.02s/it]
  8%|▊         | 43570/569592 [11:16:35<351:55:02,  2.41s/it]
                                                             

  8%|▊         | 43570/569592 [11:16:35<351:55:02,  2.41s/it]
  8%|▊         | 43571/569592 [11:16:36<287:31:45,  1.97s/it]
                                                             

  8%|▊         | 43571/569592 [11:16:36<287:31:45,  1.97s/it]
  8%|▊         | 43572/569592 [11:16:37<242:57:34,  1.66s/it]
                                                             

  8%|▊         | 43572/569592 [11:16:37<242:57:34,  1.66s/it]
  8%|▊         | 43573/569592 [11:16:40<326:51:06,  2.24s/it]
                                                             

  8%|▊         | 43573/569592 [11:16:40<326:51:06,  2.24s/it]
  8%|▊         | 43574/569592 [11:16:41<271:00:36,  1.85s/it]
                                                             

  8%|▊         | 43574/569592 [11:16:41<271:00:36,  1.85s/it]
  8%|▊         | 43575/569592 [11:16:45<336:57:59,  2.31s/it]
                                                             

  8%|▊         | 43575/569592 [11:16:45<336:57:59,  2.31s/it]
  8%|▊         | 43576/569592 [11:16:49<409:15:45,  2.80s/it]
                                                             

  8%|▊         | 43576/569592 [11:16:49<409:15:45,  2.80s/it]
  8%|▊         | 43577/569592 [11:16:52<439:06:30,  3.01s/it]
                                                             

  8%|▊         | 43577/569592 [11:16:52<439:06:30,  3.01s/it]
  8%|▊         | 43578/569592 [11:16:56<469:34:15,  3.21s/it]
                                                             

  8%|▊         | 43578/569592 [11:16:56<469:34:15,  3.21s/it]
  8%|▊         | 43579/569592 [11:16:57<370:06:27,  2.53s/it]
                                                             

  8%|▊         | 43579/569592 [11:16:57<370:06:27,  2.53s/it]
  8%|▊         | 43580/569592 [11:16:58<299:54:58,  2.05s/it]
                                                             

  8%|▊         | 43580/569592 [11:16:58<299:54:58,  2.05s/it]
  8%|▊         | 43581/569592 [11:16:59<253:18:57,  1.73s/it]
                                                             

  8%|▊         | 43581/569592 [11:16:59<253:18:57,  1.73s/it]
  8%|▊         | 43582/569592 [11:17:03<347:49:45,  2.38s/it]
                                                             

  8%|▊         | 43582/569592 [11:17:03<347:49:45,  2.38s/it]
  8%|▊         | 43583/569592 [11:17:06<416:51:35,  2.85s/it]
                                                             

  8%|▊         | 43583/569592 [11:17:07<416:51:35,  2.85s/it]
  8%|▊         | 43584/569592 [11:17:10<463:32:39,  3.17s/it]
                                                             

  8%|▊         | 43584/569592 [11:17:10<463:32:39,  3.17s/it]
  8%|▊         | 43585/569592 [11:17:14<501:07:39,  3.43s/it]
                                                             

  8%|▊         | 43585/569592 [11:17:14<501:07:39,  3.43s/it]
  8%|▊         | 43586/569592 [11:17:18<498:51:51,  3.41s/it]
                                                             

  8%|▊         | 43586/569592 [11:17:18<498:51:51,  3.41s/it]
  8%|▊         | 43587/569592 [11:17:19<389:14:45,  2.66s/it]
                                                             

  8%|▊         | 43587/569592 [11:17:19<389:14:45,  2.66s/it]
  8%|▊         | 43588/569592 [11:17:22<423:46:42,  2.90s/it]
                                                             

  8%|▊         | 43588/569592 [11:17:22<423:46:42,  2.90s/it]
  8%|▊         | 43589/569592 [11:17:23<340:28:53,  2.33s/it]
                                                             

  8%|▊         | 43589/569592 [11:17:23<340:28:53,  2.33s/it]
  8%|▊         | 43590/569592 [11:17:27<417:40:07,  2.86s/it]
                                                             

  8%|▊         | 43590/569592 [11:17:27<417:40:07,  2.86s/it]
  8%|▊         | 43591/569592 [11:17:30<433:44:32,  2.97s/it]
                                                             

  8%|▊         | 43591/569592 [11:17:31<433:44:32,  2.97s/it]
  8%|▊         | 43592/569592 [11:17:34<460:43:45,  3.15s/it]
                                                             

  8%|▊         | 43592/569592 [11:17:34<460:43:45,  3.15s/it]
  8%|▊         | 43593/569592 [11:17:35<368:05:54,  2.52s/it]
                                                             

  8%|▊         | 43593/569592 [11:17:35<368:05:54,  2.52s/it]
  8%|▊         | 43594/569592 [11:17:38<405:28:53,  2.78s/it]
                                                             

  8%|▊         | 43594/569592 [11:17:39<405:28:53,  2.78s/it]
  8%|▊         | 43595/569592 [11:17:39<324:55:35,  2.22s/it]
                                                             

  8%|▊         | 43595/569592 [11:17:39<324:55:35,  2.22s/it]
  8%|▊         | 43596/569592 [11:17:40<270:14:52,  1.85s/it]
                                                             

  8%|▊         | 43596/569592 [11:17:40<270:14:52,  1.85s/it]
  8%|▊         | 43597/569592 [11:17:44<345:23:42,  2.36s/it]
                                                             

  8%|▊         | 43597/569592 [11:17:44<345:23:42,  2.36s/it]
  8%|▊         | 43598/569592 [11:17:47<392:55:54,  2.69s/it]
                                                             

  8%|▊         | 43598/569592 [11:17:47<392:55:54,  2.69s/it]
  8%|▊         | 43599/569592 [11:17:51<421:43:23,  2.89s/it]
                                                             

  8%|▊         | 43599/569592 [11:17:51<421:43:23,  2.89s/it]
  8%|▊         | 43600/569592 [11:17:52<337:44:35,  2.31s/it]
                                                             

  8%|▊         | 43600/569592 [11:17:52<337:44:35,  2.31s/it]
  8%|▊         | 43601/569592 [11:17:53<277:37:55,  1.90s/it]
                                                             

  8%|▊         | 43601/569592 [11:17:53<277:37:55,  1.90s/it]
  8%|▊         | 43602/569592 [11:17:54<234:36:34,  1.61s/it]
                                                             

  8%|▊         | 43602/569592 [11:17:54<234:36:34,  1.61s/it]
  8%|▊         | 43603/569592 [11:17:55<205:09:25,  1.40s/it]
                                                             

  8%|▊         | 43603/569592 [11:17:55<205:09:25,  1.40s/it]
  8%|▊         | 43604/569592 [11:17:55<185:37:46,  1.27s/it]
                                                             

  8%|▊         | 43604/569592 [11:17:56<185:37:46,  1.27s/it]
  8%|▊         | 43605/569592 [11:17:58<248:28:20,  1.70s/it]
                                                             

  8%|▊         | 43605/569592 [11:17:58<248:28:20,  1.70s/it]
  8%|▊         | 43606/569592 [11:18:02<341:47:22,  2.34s/it]
                                                             

  8%|▊         | 43606/569592 [11:18:02<341:47:22,  2.34s/it]
  8%|▊         | 43607/569592 [11:18:03<280:26:31,  1.92s/it]
                                                             

  8%|▊         | 43607/569592 [11:18:03<280:26:31,  1.92s/it]
  8%|▊         | 43608/569592 [11:18:06<346:12:24,  2.37s/it]
                                                             

  8%|▊         | 43608/569592 [11:18:06<346:12:24,  2.37s/it]
  8%|▊         | 43609/569592 [11:18:10<404:40:24,  2.77s/it]
                                                             

  8%|▊         | 43609/569592 [11:18:10<404:40:24,  2.77s/it]
  8%|▊         | 43610/569592 [11:18:11<326:50:38,  2.24s/it]
                                                             

  8%|▊         | 43610/569592 [11:18:11<326:50:38,  2.24s/it]
  8%|▊         | 43611/569592 [11:18:13<308:20:26,  2.11s/it]
                                                             

  8%|▊         | 43611/569592 [11:18:13<308:20:26,  2.11s/it]
  8%|▊         | 43612/569592 [11:18:15<308:08:09,  2.11s/it]
                                                             

  8%|▊         | 43612/569592 [11:18:15<308:08:09,  2.11s/it]
  8%|▊         | 43613/569592 [11:18:18<329:37:24,  2.26s/it]
                                                             

  8%|▊         | 43613/569592 [11:18:18<329:37:24,  2.26s/it]
  8%|▊         | 43614/569592 [11:18:23<482:29:34,  3.30s/it]
                                                             

  8%|▊         | 43614/569592 [11:18:23<482:29:34,  3.30s/it]
  8%|▊         | 43615/569592 [11:18:27<491:01:06,  3.36s/it]
                                                             

  8%|▊         | 43615/569592 [11:18:27<491:01:06,  3.36s/it]
  8%|▊         | 43616/569592 [11:18:28<384:57:04,  2.63s/it]
                                                             

  8%|▊         | 43616/569592 [11:18:28<384:57:04,  2.63s/it]
  8%|▊         | 43617/569592 [11:18:31<418:10:07,  2.86s/it]
                                                             

  8%|▊         | 43617/569592 [11:18:31<418:10:07,  2.86s/it]
  8%|▊         | 43618/569592 [11:18:32<347:21:39,  2.38s/it]
                                                             

  8%|▊         | 43618/569592 [11:18:32<347:21:39,  2.38s/it]
  8%|▊         | 43619/569592 [11:18:36<399:31:54,  2.73s/it]
                                                             

  8%|▊         | 43619/569592 [11:18:36<399:31:54,  2.73s/it]
  8%|▊         | 43620/569592 [11:18:40<451:26:39,  3.09s/it]
                                                             

  8%|▊         | 43620/569592 [11:18:40<451:26:39,  3.09s/it]
  8%|▊         | 43621/569592 [11:18:44<475:40:51,  3.26s/it]
                                                             

  8%|▊         | 43621/569592 [11:18:44<475:40:51,  3.26s/it]
  8%|▊         | 43622/569592 [11:18:47<487:54:47,  3.34s/it]
                                                             

  8%|▊         | 43622/569592 [11:18:47<487:54:47,  3.34s/it]
  8%|▊         | 43623/569592 [11:18:50<483:08:38,  3.31s/it]
                                                             

  8%|▊         | 43623/569592 [11:18:50<483:08:38,  3.31s/it]
  8%|▊         | 43624/569592 [11:18:54<488:58:26,  3.35s/it]
                                                             

  8%|▊         | 43624/569592 [11:18:54<488:58:26,  3.35s/it]
  8%|▊         | 43625/569592 [11:18:58<506:41:31,  3.47s/it]
                                                             

  8%|▊         | 43625/569592 [11:18:58<506:41:31,  3.47s/it]
  8%|▊         | 43626/569592 [11:19:01<502:40:55,  3.44s/it]
                                                             

  8%|▊         | 43626/569592 [11:19:01<502:40:55,  3.44s/it]
  8%|▊         | 43627/569592 [11:19:04<503:04:23,  3.44s/it]
                                                             

  8%|▊         | 43627/569592 [11:19:04<503:04:23,  3.44s/it]
  8%|▊         | 43628/569592 [11:19:08<505:36:50,  3.46s/it]
                                                             

  8%|▊         | 43628/569592 [11:19:08<505:36:50,  3.46s/it]
  8%|▊         | 43629/569592 [11:19:11<512:30:30,  3.51s/it]
                                                             

  8%|▊         | 43629/569592 [11:19:11<512:30:30,  3.51s/it]
  8%|▊         | 43630/569592 [11:19:15<493:28:13,  3.38s/it]
                                                             

  8%|▊         | 43630/569592 [11:19:15<493:28:13,  3.38s/it]
  8%|▊         | 43631/569592 [11:19:18<488:19:16,  3.34s/it]
                                                             

  8%|▊         | 43631/569592 [11:19:18<488:19:16,  3.34s/it]
  8%|▊         | 43632/569592 [11:19:21<486:34:51,  3.33s/it]
                                                             

  8%|▊         | 43632/569592 [11:19:21<486:34:51,  3.33s/it]
  8%|▊         | 43633/569592 [11:19:25<529:21:31,  3.62s/it]
                                                             

  8%|▊         | 43633/569592 [11:19:25<529:21:31,  3.62s/it]
  8%|▊         | 43634/569592 [11:19:29<507:18:57,  3.47s/it]
                                                             

  8%|▊         | 43634/569592 [11:19:29<507:18:57,  3.47s/it]
  8%|▊         | 43635/569592 [11:19:32<494:16:44,  3.38s/it]
                                                             

  8%|▊         | 43635/569592 [11:19:32<494:16:44,  3.38s/it]
  8%|▊         | 43636/569592 [11:19:35<481:49:45,  3.30s/it]
                                                             

  8%|▊         | 43636/569592 [11:19:35<481:49:45,  3.30s/it]
  8%|▊         | 43637/569592 [11:19:38<497:52:59,  3.41s/it]
                                                             

  8%|▊         | 43637/569592 [11:19:38<497:52:59,  3.41s/it]
  8%|▊         | 43638/569592 [11:19:42<494:58:46,  3.39s/it]
                                                             

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                                               /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90021888 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
              

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  8%|▊         | 43742/569592 [11:24:24<501:00:09,  3.43s/it]
  8%|▊         | 43743/569592 [11:24:28<521:10:36,  3.57s/it]
                                                             

  8%|▊         | 43743/569592 [11:24:28<521:10:36,  3.57s/it]
  8%|▊         | 43744/569592 [11:24:29<406:26:37,  2.78s/it]
                                                             

  8%|▊         | 43744/569592 [11:24:29<406:26:37,  2.78s/it]
  8%|▊         | 43745/569592 [11:24:32<438:52:11,  3.00s/it]
                                                             

  8%|▊         | 43745/569592 [11:24:32<438:52:11,  3.00s/it]
  8%|▊         | 43746/569592 [11:24:37<523:11:46,  3.58s/it]
                                                             

  8%|▊         | 43746/569592 [11:24:37<523:11:46,  3.58s/it]
  8%|▊         | 43747/569592 [11:24:40<505:12:23,  3.46s/it]
                                                             

  8%|▊         | 43747/569592 [11:24:40<505:12:23,  3.46s/it]
  8%|▊         | 43748/569592 [11:24:43<498:42:18,  3.41s/it]
                                                             

  8%|▊         | 43748/569592 [11:24:43<498:42:18,  3.41s/it]
  8%|▊         | 43749/569592 [11:24:44<389:33:09,  2.67s/it]
                                                             

  8%|▊         | 43749/569592 [11:24:44<389:33:09,  2.67s/it]
  8%|▊         | 43750/569592 [11:24:48<426:08:17,  2.92s/it]
                                                             

  8%|▊         | 43750/569592 [11:24:48<426:08:17,  2.92s/it]
  8%|▊         | 43751/569592 [11:24:52<457:40:18,  3.13s/it]
                                                             

  8%|▊         | 43751/569592 [11:24:52<457:40:18,  3.13s/it]
  8%|▊         | 43752/569592 [11:24:55<459:48:09,  3.15s/it]
                                                             

  8%|▊         | 43752/569592 [11:24:55<459:48:09,  3.15s/it]
  8%|▊         | 43753/569592 [11:24:59<509:14:44,  3.49s/it]
                                                             

  8%|▊         | 43753/569592 [11:24:59<509:14:44,  3.49s/it]
  8%|▊         | 43754/569592 [11:25:03<538:23:47,  3.69s/it]
                                                             

  8%|▊         | 43754/569592 [11:25:03<538:23:47,  3.69s/it]
  8%|▊         | 43755/569592 [11:25:06<518:47:03,  3.55s/it]
                                                             

  8%|▊         | 43755/569592 [11:25:06<518:47:03,  3.55s/it]
  8%|▊         | 43756/569592 [11:25:11<549:48:36,  3.76s/it]
                                                             

  8%|▊         | 43756/569592 [11:25:11<549:48:36,  3.76s/it]
  8%|▊         | 43757/569592 [11:25:14<537:28:09,  3.68s/it]
                                                             

  8%|▊         | 43757/569592 [11:25:14<537:28:09,  3.68s/it]
  8%|▊         | 43758/569592 [11:25:17<506:58:44,  3.47s/it]
                                                             

  8%|▊         | 43758/569592 [11:25:17<506:58:44,  3.47s/it]
  8%|▊         | 43759/569592 [11:25:21<505:41:12,  3.46s/it]
                                                             

  8%|▊         | 43759/569592 [11:25:21<505:41:12,  3.46s/it]
  8%|▊         | 43760/569592 [11:25:22<395:43:52,  2.71s/it]
                                                             

  8%|▊         | 43760/569592 [11:25:22<395:43:52,  2.71s/it]
  8%|▊         | 43761/569592 [11:25:23<321:38:40,  2.20s/it]
                                                             

  8%|▊         | 43761/569592 [11:25:23<321:38:40,  2.20s/it]
  8%|▊         | 43762/569592 [11:25:26<390:27:48,  2.67s/it]
                                                             

  8%|▊         | 43762/569592 [11:25:26<390:27:48,  2.67s/it]
  8%|▊         | 43763/569592 [11:25:27<319:42:03,  2.19s/it]
                                                             

  8%|▊         | 43763/569592 [11:25:27<319:42:03,  2.19s/it]
  8%|▊         | 43764/569592 [11:25:28<269:42:12,  1.85s/it]
                                                             

  8%|▊         | 43764/569592 [11:25:28<269:42:12,  1.85s/it]
  8%|▊         | 43765/569592 [11:25:32<356:47:33,  2.44s/it]
                                                             

  8%|▊         | 43765/569592 [11:25:32<356:47:33,  2.44s/it]
  8%|▊         | 43766/569592 [11:25:36<395:51:19,  2.71s/it]
                                                             

  8%|▊         | 43766/569592 [11:25:36<395:51:19,  2.71s/it]
  8%|▊         | 43767/569592 [11:25:39<442:49:10,  3.03s/it]
                                                             

  8%|▊         | 43767/569592 [11:25:39<442:49:10,  3.03s/it]
  8%|▊         | 43768/569592 [11:25:43<472:08:44,  3.23s/it]
                                                             

  8%|▊         | 43768/569592 [11:25:43<472:08:44,  3.23s/it]
  8%|▊         | 43769/569592 [11:25:46<463:15:25,  3.17s/it]
                                                             

  8%|▊         | 43769/569592 [11:25:46<463:15:25,  3.17s/it]
  8%|▊         | 43770/569592 [11:25:49<469:30:57,  3.21s/it]
                                                             

  8%|▊         | 43770/569592 [11:25:49<469:30:57,  3.21s/it]
  8%|▊         | 43771/569592 [11:25:53<472:09:47,  3.23s/it]
                                                             

  8%|▊         | 43771/569592 [11:25:53<472:09:47,  3.23s/it]
  8%|▊         | 43772/569592 [11:25:56<479:52:29,  3.29s/it]
                                                             

  8%|▊         | 43772/569592 [11:25:56<479:52:29,  3.29s/it]
  8%|▊         | 43773/569592 [11:25:59<480:11:59,  3.29s/it]
                                                             

  8%|▊         | 43773/569592 [11:25:59<480:11:59,  3.29s/it]
  8%|▊         | 43774/569592 [11:26:03<483:34:20,  3.31s/it]
                                                             

  8%|▊         | 43774/569592 [11:26:03<483:34:20,  3.31s/it]
  8%|▊         | 43775/569592 [11:26:06<483:02:33,  3.31s/it]
                                                             

  8%|▊         | 43775/569592 [11:26:06<483:02:33,  3.31s/it]
  8%|▊         | 43776/569592 [11:26:09<486:25:47,  3.33s/it]
                                                             

  8%|▊         | 43776/569592 [11:26:09<486:25:47,  3.33s/it]
  8%|▊         | 43777/569592 [11:26:10<380:16:58,  2.60s/it]
                                                             

  8%|▊         | 43777/569592 [11:26:10<380:16:58,  2.60s/it]
  8%|▊         | 43778/569592 [11:26:15<488:37:56,  3.35s/it]
                                                             

  8%|▊         | 43778/569592 [11:26:15<488:37:56,  3.35s/it]
  8%|▊         | 43779/569592 [11:26:16<382:15:03,  2.62s/it]
                                                             

  8%|▊         | 43779/569592 [11:26:16<382:15:03,  2.62s/it]
  8%|▊         | 43780/569592 [11:26:20<415:07:13,  2.84s/it]
                                                             

  8%|▊         | 43780/569592 [11:26:20<415:07:13,  2.84s/it]
  8%|▊         | 43781/569592 [11:26:23<456:09:37,  3.12s/it]
                                                             

  8%|▊         | 43781/569592 [11:26:23<456:09:37,  3.12s/it]
  8%|▊         | 43782/569592 [11:26:27<472:02:33,  3.23s/it]
                                                             

  8%|▊         | 43782/569592 [11:26:27<472:02:33,  3.23s/it]
  8%|▊         | 43783/569592 [11:26:30<468:24:18,  3.21s/it]
                                                             

  8%|▊         | 43783/569592 [11:26:30<468:24:18,  3.21s/it]
  8%|▊         | 43784/569592 [11:26:33<475:27:08,  3.26s/it]
                                                             

  8%|▊         | 43784/569592 [11:26:33<475:27:08,  3.26s/it]
  8%|▊         | 43785/569592 [11:26:35<378:38:52,  2.59s/it]
                                                             

  8%|▊         | 43785/569592 [11:26:35<378:38:52,  2.59s/it]
  8%|▊         | 43786/569592 [11:26:38<419:15:42,  2.87s/it]
                                                             

  8%|▊         | 43786/569592 [11:26:38<419:15:42,  2.87s/it]
  8%|▊         | 43787/569592 [11:26:39<335:35:42,  2.30s/it]
                                                             

  8%|▊         | 43787/569592 [11:26:39<335:35:42,  2.30s/it]
  8%|▊         | 43788/569592 [11:26:40<279:33:08,  1.91s/it]
                                                             

  8%|▊         | 43788/569592 [11:26:40<279:33:08,  1.91s/it]
  8%|▊         | 43789/569592 [11:26:41<236:42:37,  1.62s/it]
                                                             

  8%|▊         | 43789/569592 [11:26:41<236:42:37,  1.62s/it]
  8%|▊         | 43790/569592 [11:26:45<320:58:43,  2.20s/it]
                                                             

  8%|▊         | 43790/569592 [11:26:45<320:58:43,  2.20s/it]
  8%|▊         | 43791/569592 [11:26:48<393:08:32,  2.69s/it]
                                                             

  8%|▊         | 43791/569592 [11:26:48<393:08:32,  2.69s/it]
  8%|▊         | 43792/569592 [11:26:49<319:26:28,  2.19s/it]
                                                             

  8%|▊         | 43792/569592 [11:26:49<319:26:28,  2.19s/it]
  8%|▊         | 43793/569592 [11:26:53<390:51:48,  2.68s/it]
                                                             

  8%|▊         | 43793/569592 [11:26:53<390:51:48,  2.68s/it]
  8%|▊         | 43794/569592 [11:26:54<318:01:46,  2.18s/it]
                                                             

  8%|▊         | 43794/569592 [11:26:54<318:01:46,  2.18s/it]
  8%|▊         | 43795/569592 [11:26:58<389:57:35,  2.67s/it]
                                                             

  8%|▊         | 43795/569592 [11:26:58<389:57:35,  2.67s/it]
  8%|▊         | 43796/569592 [11:27:02<443:41:57,  3.04s/it]
                                                             

  8%|▊         | 43796/569592 [11:27:02<443:41:57,  3.04s/it]
  8%|▊         | 43797/569592 [11:27:05<466:50:08,  3.20s/it]
                                                             

  8%|▊         | 43797/569592 [11:27:05<466:50:08,  3.20s/it]
  8%|▊         | 43798/569592 [11:27:06<367:48:24,  2.52s/it]
                                                             

  8%|▊         | 43798/569592 [11:27:06<367:48:24,  2.52s/it]
  8%|▊         | 43799/569592 [11:27:07<298:35:31,  2.04s/it]
                                                             

  8%|▊         | 43799/569592 [11:27:07<298:35:31,  2.04s/it]
  8%|▊         | 43800/569592 [11:27:12<392:33:37,  2.69s/it]
                                                             

  8%|▊         | 43800/569592 [11:27:12<392:33:37,  2.69s/it]
  8%|▊         | 43801/569592 [11:27:15<432:25:32,  2.96s/it]
                                                             

  8%|▊         | 43801/569592 [11:27:15<432:25:32,  2.96s/it]
  8%|▊         | 43802/569592 [11:27:19<479:52:51,  3.29s/it]
                                                             

  8%|▊         | 43802/569592 [11:27:19<479:52:51,  3.29s/it]
  8%|▊         | 43803/569592 [11:27:22<473:50:12,  3.24s/it]
                                                             

  8%|▊         | 43803/569592 [11:27:22<473:50:12,  3.24s/it]
  8%|▊         | 43804/569592 [11:27:26<494:46:21,  3.39s/it]
                                                             

  8%|▊         | 43804/569592 [11:27:26<494:46:21,  3.39s/it]
  8%|▊         | 43805/569592 [11:27:29<496:43:50,  3.40s/it]
                                                             

  8%|▊         | 43805/569592 [11:27:29<496:43:50,  3.40s/it]
  8%|▊         | 43806/569592 [11:27:30<389:41:19,  2.67s/it]
                                                             

  8%|▊         | 43806/569592 [11:27:30<389:41:19,  2.67s/it]
  8%|▊         | 43807/569592 [11:27:34<415:25:49,  2.84s/it]
                                                             

  8%|▊         | 43807/569592 [11:27:34<415:25:49,  2.84s/it]
  8%|▊         | 43808/569592 [11:27:37<432:27:14,  2.96s/it]
                                                             

  8%|▊         | 43808/569592 [11:27:37<432:27:14,  2.96s/it]
  8%|▊         | 43809/569592 [11:27:40<443:04:31,  3.03s/it]
                                                             

  8%|▊         | 43809/569592 [11:27:40<443:04:31,  3.03s/it]
  8%|▊         | 43810/569592 [11:27:44<470:59:16,  3.22s/it]
                                                             

  8%|▊         | 43810/569592 [11:27:44<470:59:16,  3.22s/it]
  8%|▊         | 43811/569592 [11:27:47<472:32:45,  3.24s/it]
                                                             

  8%|▊         | 43811/569592 [11:27:47<472:32:45,  3.24s/it]
  8%|▊         | 43812/569592 [11:27:48<370:25:40,  2.54s/it]
                                                             

  8%|▊         | 43812/569592 [11:27:48<370:25:40,  2.54s/it]
  8%|▊         | 43813/569592 [11:27:49<302:19:46,  2.07s/it]
                                                             

  8%|▊         | 43813/569592 [11:27:49<302:19:46,  2.07s/it]
  8%|▊         | 43814/569592 [11:27:50<252:54:27,  1.73s/it]
                                                             

  8%|▊         | 43814/569592 [11:27:50<252:54:27,  1.73s/it]
  8%|▊         | 43815/569592 [11:27:51<217:51:34,  1.49s/it]
                                                             

  8%|▊         | 43815/569592 [11:27:51<217:51:34,  1.49s/it]
  8%|▊         | 43816/569592 [11:27:55<315:22:26,  2.16s/it]
                                                             

  8%|▊         | 43816/569592 [11:27:55<315:22:26,  2.16s/it]
  8%|▊         | 43817/569592 [11:27:58<371:28:48,  2.54s/it]
                                                             

  8%|▊         | 43817/569592 [11:27:58<371:28:48,  2.54s/it]
  8%|▊         | 43818/569592 [11:28:01<405:46:47,  2.78s/it]
                                                             

  8%|▊         | 43818/569592 [11:28:01<405:46:47,  2.78s/it]
  8%|▊         | 43819/569592 [11:28:02<327:26:45,  2.24s/it]
                                                             

  8%|▊         | 43819/569592 [11:28:02<327:26:45,  2.24s/it]
  8%|▊         | 43820/569592 [11:28:06<394:36:09,  2.70s/it]
                                                             

  8%|▊         | 43820/569592 [11:28:06<394:36:09,  2.70s/it]
  8%|▊         | 43821/569592 [11:28:10<444:51:08,  3.05s/it]
                                                             

  8%|▊         | 43821/569592 [11:28:10<444:51:08,  3.05s/it]
  8%|▊         | 43822/569592 [11:28:14<496:02:44,  3.40s/it]
                                                             

  8%|▊         | 43822/569592 [11:28:14<496:02:44,  3.40s/it]
  8%|▊         | 43823/569592 [11:28:15<391:38:57,  2.68s/it]
                                                             

  8%|▊         | 43823/569592 [11:28:15<391:38:57,  2.68s/it]
  8%|▊         | 43824/569592 [11:28:18<420:56:32,  2.88s/it]
                                                             

  8%|▊         | 43824/569592 [11:28:19<420:56:32,  2.88s/it]
  8%|▊         | 43825/569592 [11:28:19<336:28:38,  2.30s/it]
                                                             

  8%|▊         | 43825/569592 [11:28:19<336:28:38,  2.30s/it]
  8%|▊         | 43826/569592 [11:28:23<391:13:50,  2.68s/it]
                                                             

  8%|▊         | 43826/569592 [11:28:23<391:13:50,  2.68s/it]
  8%|▊         | 43827/569592 [11:28:26<425:03:45,  2.91s/it]
                                                             

  8%|▊         | 43827/569592 [11:28:26<425:03:45,  2.91s/it]
  8%|▊         | 43828/569592 [11:28:27<342:15:36,  2.34s/it]
                                                             

  8%|▊         | 43828/569592 [11:28:27<342:15:36,  2.34s/it]
  8%|▊         | 43829/569592 [11:28:28<282:40:01,  1.94s/it]
                                                             

  8%|▊         | 43829/569592 [11:28:28<282:40:01,  1.94s/it]
  8%|▊         | 43830/569592 [11:28:29<240:13:04,  1.64s/it]
                                                             

  8%|▊         | 43830/569592 [11:28:29<240:13:04,  1.64s/it]
  8%|▊         | 43831/569592 [11:28:30<209:12:26,  1.43s/it]
                                                             

  8%|▊         | 43831/569592 [11:28:30<209:12:26,  1.43s/it]
  8%|▊         | 43832/569592 [11:28:32<200:07:53,  1.37s/it]
                                                             

  8%|▊         | 43832/569592 [11:28:32<200:07:53,  1.37s/it]
  8%|▊         | 43833/569592 [11:28:35<291:10:18,  1.99s/it]
                                                             

  8%|▊         | 43833/569592 [11:28:35<291:10:18,  1.99s/it]
  8%|▊         | 43834/569592 [11:28:36<248:01:43,  1.70s/it]
                                                             

  8%|▊         | 43834/569592 [11:28:36<248:01:43,  1.70s/it]
  8%|▊         | 43835/569592 [11:28:40<338:23:51,  2.32s/it]
                                                             

  8%|▊         | 43835/569592 [11:28:40<338:23:51,  2.32s/it]
  8%|▊         | 43836/569592 [11:28:42<352:56:35,  2.42s/it]
                                                             

  8%|▊         | 43836/569592 [11:28:42<352:56:35,  2.42s/it]
  8%|▊         | 43837/569592 [11:28:46<401:44:23,  2.75s/it]
                                                             

  8%|▊         | 43837/569592 [11:28:46<401:44:23,  2.75s/it]
  8%|▊         | 43838/569592 [11:28:49<426:26:58,  2.92s/it]
                                                             

  8%|▊         | 43838/569592 [11:28:49<426:26:58,  2.92s/it]
  8%|▊         | 43839/569592 [11:28:50<341:54:53,  2.34s/it]
                                                             

  8%|▊         | 43839/569592 [11:28:50<341:54:53,  2.34s/it]
  8%|▊         | 43840/569592 [11:28:54<388:30:20,  2.66s/it]
                                                             

  8%|▊         | 43840/569592 [11:28:54<388:30:20,  2.66s/it]
  8%|▊         | 43841/569592 [11:28:57<429:45:09,  2.94s/it]
                                                             

  8%|▊         | 43841/569592 [11:28:57<429:45:09,  2.94s/it]
  8%|▊         | 43842/569592 [11:28:58<342:24:32,  2.34s/it]
                                                             

  8%|▊         | 43842/569592 [11:28:58<342:24:32,  2.34s/it]
  8%|▊         | 43843/569592 [11:29:02<386:22:49,  2.65s/it]
                                                             

  8%|▊         | 43843/569592 [11:29:02<386:22:49,  2.65s/it]
  8%|▊         | 43844/569592 [11:29:06<450:07:49,  3.08s/it]
                                                             

  8%|▊         | 43844/569592 [11:29:06<450:07:49,  3.08s/it]
  8%|▊         | 43845/569592 [11:29:10<503:21:44,  3.45s/it]
                                                             

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  8%|▊         | 438/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (96562176 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  8%|▊    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (101267328 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  8%|▊         | 44000/569592 [11:36:12<466:00:03,  3.19s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-44000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-44000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-44000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-44000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-44000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-44000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-43000] due to args.save_total_limit

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  8%|▊         | 44048/569592 [11:40:25<205:00:27,  1.40s/it]
  8%|▊         | 44049/569592 [11:40:29<304:09:53,  2.08s/it]
                                                             

  8%|▊         | 44049/569592 [11:40:30<304:09:53,  2.08s/it]
  8%|▊         | 44050/569592 [11:40:33<369:59:14,  2.53s/it]
                                                             

  8%|▊         | 44050/569592 [11:40:33<369:59:14,  2.53s/it]
  8%|▊         | 44051/569592 [11:40:34<300:15:51,  2.06s/it]
                                                             

  8%|▊         | 44051/569592 [11:40:34<300:15:51,  2.06s/it]
  8%|▊         | 44052/569592 [11:40:38<414:48:03,  2.84s/it]
                                                             

  8%|▊         | 44052/569592 [11:40:38<414:48:03,  2.84s/it]
  8%|▊         | 44053/569592 [11:40:42<456:22:11,  3.13s/it]
                                                             

  8%|▊         | 44053/569592 [11:40:42<456:22:11,  3.13s/it]
  8%|▊         | 44054/569592 [11:40:46<473:28:46,  3.24s/it]
                                                             

  8%|▊         | 44054/569592 [11:40:46<473:28:46,  3.24s/it]
  8%|▊         | 44055/569592 [11:40:50<509:54:28,  3.49s/it]
                                                             

  8%|▊         | 44055/569592 [11:40:50<509:54:28,  3.49s/it]
  8%|▊         | 44056/569592 [11:40:51<397:49:16,  2.73s/it]
                                                             

  8%|▊         | 44056/569592 [11:40:51<397:49:16,  2.73s/it]
  8%|▊         | 44057/569592 [11:40:54<425:53:12,  2.92s/it]
                                                             

  8%|▊         | 44057/569592 [11:40:54<425:53:12,  2.92s/it]
  8%|▊         | 44058/569592 [11:40:57<443:31:55,  3.04s/it]
                                                             

  8%|▊         | 44058/569592 [11:40:57<443:31:55,  3.04s/it]
  8%|▊         | 44059/569592 [11:40:58<353:04:13,  2.42s/it]
                                                             

  8%|▊         | 44059/569592 [11:40:58<353:04:13,  2.42s/it]
  8%|▊         | 44060/569592 [11:41:02<419:01:42,  2.87s/it]
                                                             

  8%|▊         | 44060/569592 [11:41:02<419:01:42,  2.87s/it]
  8%|▊         | 44061/569592 [11:41:03<335:27:54,  2.30s/it]
                                                             

  8%|▊         | 44061/569592 [11:41:03<335:27:54,  2.30s/it]
  8%|▊         | 44062/569592 [11:41:04<277:59:16,  1.90s/it]
                                                             

  8%|▊         | 44062/569592 [11:41:04<277:59:16,  1.90s/it]
  8%|▊         | 44063/569592 [11:41:05<236:00:58,  1.62s/it]
                                                             

  8%|▊         | 44063/569592 [11:41:05<236:00:58,  1.62s/it]
  8%|▊         | 44064/569592 [11:41:07<233:07:01,  1.60s/it]
                                                             

  8%|▊         | 44064/569592 [11:41:07<233:07:01,  1.60s/it]
  8%|▊         | 44065/569592 [11:41:10<330:30:15,  2.26s/it]
                                                             

  8%|▊         | 44065/569592 [11:41:10<330:30:15,  2.26s/it]
  8%|▊         | 44066/569592 [11:41:11<271:42:01,  1.86s/it]
                                                             

  8%|▊         | 44066/569592 [11:41:11<271:42:01,  1.86s/it]
  8%|▊         | 44067/569592 [11:41:15<360:56:11,  2.47s/it]
                                                             

  8%|▊         | 44067/569592 [11:41:15<360:56:11,  2.47s/it]
  8%|▊         | 44068/569592 [11:41:19<397:13:15,  2.72s/it]
                                                             

  8%|▊         | 44068/569592 [11:41:19<397:13:15,  2.72s/it]
  8%|▊         | 44069/569592 [11:41:20<318:53:43,  2.18s/it]
                                                             

  8%|▊         | 44069/569592 [11:41:20<318:53:43,  2.18s/it]
  8%|▊         | 44070/569592 [11:41:20<263:59:07,  1.81s/it]
                                                             

  8%|▊         | 44070/569592 [11:41:20<263:59:07,  1.81s/it]
  8%|▊         | 44071/569592 [11:41:23<275:12:08,  1.89s/it]
                                                             

  8%|▊         | 44071/569592 [11:41:23<275:12:08,  1.89s/it]
  8%|▊         | 44072/569592 [11:41:28<422:31:31,  2.89s/it]
                                                             

  8%|▊         | 44072/569592 [11:41:28<422:31:31,  2.89s/it]
  8%|▊         | 44073/569592 [11:41:31<444:23:31,  3.04s/it]
                                                             

  8%|▊         | 44073/569592 [11:41:31<444:23:31,  3.04s/it]
  8%|▊         | 44074/569592 [11:41:32<353:17:09,  2.42s/it]
                                                             

  8%|▊         | 44074/569592 [11:41:32<353:17:09,  2.42s/it]
  8%|▊         | 44075/569592 [11:41:33<288:16:06,  1.97s/it]
                                                             

  8%|▊         | 44075/569592 [11:41:33<288:16:06,  1.97s/it]
  8%|▊         | 44076/569592 [11:41:38<409:26:52,  2.80s/it]
                                                             

  8%|▊         | 44076/569592 [11:41:38<409:26:52,  2.80s/it]
  8%|▊         | 44077/569592 [11:41:41<436:12:57,  2.99s/it]
                                                             

  8%|▊         | 44077/569592 [11:41:41<436:12:57,  2.99s/it]
  8%|▊         | 44078/569592 [11:41:45<465:55:02,  3.19s/it]
                                                             

  8%|▊         | 44078/569592 [11:41:45<465:55:02,  3.19s/it]
  8%|▊         | 44079/569592 [11:41:46<368:38:23,  2.53s/it]
                                                             

  8%|▊         | 44079/569592 [11:41:46<368:38:23,  2.53s/it]
  8%|▊         | 44080/569592 [11:41:49<401:12:27,  2.75s/it]
                                                             

  8%|▊         | 44080/569592 [11:41:49<401:12:27,  2.75s/it]
  8%|▊         | 44081/569592 [11:41:54<474:00:41,  3.25s/it]
                                                             

  8%|▊         | 44081/569592 [11:41:54<474:00:41,  3.25s/it]
  8%|▊         | 44082/569592 [11:41:58<504:31:04,  3.46s/it]
                                                             

  8%|▊         | 44082/569592 [11:41:58<504:31:04,  3.46s/it]
  8%|▊         | 44083/569592 [11:41:58<393:42:55,  2.70s/it]
                                                             

  8%|▊         | 44083/569592 [11:41:58<393:42:55,  2.70s/it]
  8%|▊         | 44084/569592 [11:42:02<451:16:06,  3.09s/it]
                                                             

  8%|▊         | 44084/569592 [11:42:02<451:16:06,  3.09s/it]
  8%|▊         | 44085/569592 [11:42:03<356:19:58,  2.44s/it]
                                                             

  8%|▊         | 44085/569592 [11:42:03<356:19:58,  2.44s/it]
  8%|▊         | 44086/569592 [11:42:04<291:03:38,  1.99s/it]
                                                             

  8%|▊         | 44086/569592 [11:42:04<291:03:38,  1.99s/it]
  8%|▊         | 44087/569592 [11:42:08<369:27:02,  2.53s/it]
                                                             

  8%|▊         | 44087/569592 [11:42:08<369:27:02,  2.53s/it]
  8%|▊         | 44088/569592 [11:42:12<426:58:29,  2.93s/it]
                                                             

  8%|▊         | 44088/569592 [11:42:12<426:58:29,  2.93s/it]
  8%|▊         | 44089/569592 [11:42:16<468:15:35,  3.21s/it]
                                                             

  8%|▊         | 44089/569592 [11:42:16<468:15:35,  3.21s/it]
  8%|▊         | 44090/569592 [11:42:19<472:42:37,  3.24s/it]
                                                             

  8%|▊         | 44090/569592 [11:42:19<472:42:37,  3.24s/it]
  8%|▊         | 44091/569592 [11:42:23<489:28:04,  3.35s/it]
                                                             

  8%|▊         | 44091/569592 [11:42:23<489:28:04,  3.35s/it]
  8%|▊         | 44092/569592 [11:42:26<480:09:35,  3.29s/it]
                                                             

  8%|▊         | 44092/569592 [11:42:26<480:09:35,  3.29s/it]
  8%|▊         | 44093/569592 [11:42:29<484:18:21,  3.32s/it]
                                                             

  8%|▊         | 44093/569592 [11:42:29<484:18:21,  3.32s/it]
  8%|▊         | 44094/569592 [11:42:33<502:57:08,  3.45s/it]
                                                             

  8%|▊         | 44094/569592 [11:42:33<502:57:08,  3.45s/it]
  8%|▊         | 44095/569592 [11:42:36<500:56:51,  3.43s/it]
                                                             

  8%|▊         | 44095/569592 [11:42:36<500:56:51,  3.43s/it]
  8%|▊         | 44096/569592 [11:42:41<561:33:46,  3.85s/it]
                                                             

  8%|▊         | 44096/569592 [11:42:41<561:33:46,  3.85s/it]
  8%|▊         | 44097/569592 [11:42:45<563:30:03,  3.86s/it]
                                                             

  8%|▊         | 44097/569592 [11:42:45<563:30:03,  3.86s/it]
  8%|▊         | 44098/569592 [11:42:48<533:47:15,  3.66s/it]
                                                             

  8%|▊         | 44098/569592 [11:42:48<533:47:15,  3.66s/it]
  8%|▊         | 44099/569592 [11:42:49<412:45:12,  2.83s/it]
                                                             

  8%|▊         | 44099/569592 [11:42:49<412:45:12,  2.83s/it]
  8%|▊         | 44100/569592 [11:42:50<328:38:51,  2.25s/it]
                                                             

  8%|▊         | 44100/569592 [11:42:50<328:38:51,  2.25s/it]
  8%|▊         | 44101/569592 [11:42:54<420:28:40,  2.88s/it]
                                                             

  8%|▊         | 44101/569592 [11:42:54<420:28:40,  2.88s/it]
  8%|▊         | 44102/569592 [11:42:59<476:23:34,  3.26s/it]
                                                             

  8%|▊         | 44102/569592 [11:42:59<476:23:34,  3.26s/it]
  8%|▊         | 44103/569592 [11:43:02<492:48:31,  3.38s/it]
                                                             

  8%|▊         | 44103/569592 [11:43:02<492:48:31,  3.38s/it]
  8%|▊         | 44104/569592 [11:43:03<384:38:40,  2.64s/it]
                                                             

  8%|▊         | 44104/569592 [11:43:03<384:38:40,  2.64s/it]
  8%|▊         | 44105/569592 [11:43:07<438:21:10,  3.00s/it]
                                                             

  8%|▊         | 44105/569592 [11:43:07<438:21:10,  3.00s/it]
  8%|▊         | 44106/569592 [11:43:10<446:26:03,  3.06s/it]
                                                             

  8%|▊         | 44106/569592 [11:43:10<446:26:03,  3.06s/it]
  8%|▊         | 44107/569592 [11:43:14<474:52:46,  3.25s/it]
                                                             

  8%|▊         | 44107/569592 [11:43:14<474:52:46,  3.25s/it]
  8%|▊         | 44108/569592 [11:43:15<372:46:34,  2.55s/it]
                                                             

  8%|▊         | 44108/569592 [11:43:15<372:46:34,  2.55s/it]
  8%|▊         | 44109/569592 [11:43:16<302:52:42,  2.07s/it]
                                                             

  8%|▊         | 44109/569592 [11:43:16<302:52:42,  2.07s/it]
  8%|▊         | 44110/569592 [11:43:20<396:19:00,  2.72s/it]
                                                             

  8%|▊         | 44110/569592 [11:43:20<396:19:00,  2.72s/it]
  8%|▊         | 44111/569592 [11:43:24<461:54:11,  3.16s/it]
                                                             

  8%|▊         | 44111/569592 [11:43:24<461:54:11,  3.16s/it]
  8%|▊         | 44112/569592 [11:43:25<362:48:31,  2.49s/it]
                                                             

  8%|▊         | 44112/569592 [11:43:25<362:48:31,  2.49s/it]
  8%|▊         | 44113/569592 [11:43:29<441:29:30,  3.02s/it]
                                                             

  8%|▊         | 44113/569592 [11:43:29<441:29:30,  3.02s/it]
  8%|▊         | 44114/569592 [11:43:33<450:20:42,  3.09s/it]
                                                             

  8%|▊         | 44114/569592 [11:43:33<450:20:42,  3.09s/it]
  8%|▊         | 44115/569592 [11:43:36<471:21:00,  3.23s/it]
                                                             

  8%|▊         | 44115/569592 [11:43:36<471:21:00,  3.23s/it]
  8%|▊         | 44116/569592 [11:43:39<474:38:23,  3.25s/it]
                                                             

  8%|▊         | 44116/569592 [11:43:39<474:38:23,  3.25s/it]
  8%|▊         | 44117/569592 [11:43:43<495:07:01,  3.39s/it]
                                                             

  8%|▊         | 44117/569592 [11:43:43<495:07:01,  3.39s/it]
  8%|▊         | 44118/569592 [11:43:47<508:08:28,  3.48s/it]
                                                             

  8%|▊         | 44118/569592 [11:43:47<508:08:28,  3.48s/it]
  8%|▊         | 44119/569592 [11:43:50<494:00:27,  3.38s/it]
                                                             

  8%|▊         | 44119/569592 [11:43:50<494:00:27,  3.38s/it]
  8%|▊         | 44120/569592 [11:43:53<487:11:18,  3.34s/it]
                                                             

  8%|▊         | 44120/569592 [11:43:53<487:11:18,  3.34s/it]
  8%|▊         | 44121/569592 [11:43:57<486:54:53,  3.34s/it]
                                                             

  8%|▊         | 44121/569592 [11:43:57<486:54:53,  3.34s/it]
  8%|▊         | 44122/569592 [11:43:58<381:03:30,  2.61s/it]
                                                             

  8%|▊         | 44122/569592 [11:43:58<381:03:30,  2.61s/it]
  8%|▊         | 44123/569592 [11:43:59<309:36:55,  2.12s/it]
                                                             

  8%|▊         | 44123/569592 [11:43:59<309:36:55,  2.12s/it]
  8%|▊         | 44124/569592 [11:44:02<384:03:36,  2.63s/it]
                                                             

  8%|▊         | 44124/569592 [11:44:02<384:03:36,  2.63s/it]
  8%|▊         | 44125/569592 [11:44:06<425:43:43,  2.92s/it]
                                                             

  8%|▊         | 44125/569592 [11:44:06<425:43:43,  2.92s/it]
  8%|▊         | 44126/569592 [11:44:10<457:13:20,  3.13s/it]
                                                             

  8%|▊         | 44126/569592 [11:44:10<457:13:20,  3.13s/it]
  8%|▊         | 44127/569592 [11:44:13<489:01:06,  3.35s/it]
                                                             

  8%|▊         | 44127/569592 [11:44:13<489:01:06,  3.35s/it]
  8%|▊         | 44128/569592 [11:44:14<381:26:25,  2.61s/it]
                                                             

  8%|▊         | 44128/569592 [11:44:14<381:26:25,  2.61s/it]
  8%|▊         | 44129/569592 [11:44:18<431:57:49,  2.96s/it]
                                                             

  8%|▊         | 44129/569592 [11:44:18<431:57:49,  2.96s/it]
  8%|▊         | 44130/569592 [11:44:22<458:00:28,  3.14s/it]
                                                             

  8%|▊         | 44130/569592 [11:44:22<458:00:28,  3.14s/it]
  8%|▊         | 44131/569592 [11:44:25<473:41:21,  3.25s/it]
                                                             

  8%|▊         | 44131/569592 [11:44:25<473:41:21,  3.25s/it]
  8%|▊         | 44132/569592 [11:44:29<483:57:54,  3.32s/it]
                                                             

  8%|▊         | 44132/569592 [11:44:29<483:57:54,  3.32s/it]
  8%|▊         | 44133/569592 [11:44:32<507:02:19,  3.47s/it]
                                                             

  8%|▊         | 44133/569592 [11:44:32<507:02:19,  3.47s/it]
  8%|▊         | 44134/569592 [11:44:33<393:37:47,  2.70s/it]
                                                             

  8%|▊         | 44134/569592 [11:44:33<393:37:47,  2.70s/it]
  8%|▊         | 44135/569592 [11:44:37<433:54:56,  2.97s/it]
                                                             

  8%|▊         | 44135/569592 [11:44:37<433:54:56,  2.97s/it]
  8%|▊         | 44136/569592 [11:44:38<345:14:24,  2.37s/it]
                                                             

  8%|▊         | 44136/569592 [11:44:38<345:14:24,  2.37s/it]
  8%|▊         | 44137/569592 [11:44:42<408:06:59,  2.80s/it]
                                                             

  8%|▊         | 44137/569592 [11:44:42<408:06:59,  2.80s/it]
  8%|▊         | 44138/569592 [11:44:43<329:00:00,  2.25s/it]
                                                             

  8%|▊         | 44138/569592 [11:44:43<329:00:00,  2.25s/it]
  8%|▊         | 44139/569592 [11:44:49<496:17:50,  3.40s/it]
                                                             

  8%|▊         | 44139/569592 [11:44:49<496:17:50,  3.40s/it]
  8%|▊         | 44140/569592 [11:44:53<517:22:28,  3.54s/it]
                                                             

  8%|▊         | 44140/569592 [11:44:53<517:22:28,  3.54s/it]
  8%|▊         | 44141/569592 [11:44:56<518:16:45,  3.55s/it]
                                                             

  8%|▊         | 44141/569592 [11:44:56<518:16:45,  3.55s/it]
  8%|▊         | 44142/569592 [11:44:57<401:56:36,  2.75s/it]
                                                             

  8%|▊         | 44142/569592 [11:44:57<401:56:36,  2.75s/it]
  8%|▊         | 44143/569592 [11:45:00<423:31:54,  2.90s/it]
                                                             

  8%|▊         | 44143/569592 [11:45:00<423:31:54,  2.90s/it]
  8%|▊         | 44144/569592 [11:45:04<449:59:45,  3.08s/it]
                                                             

  8%|▊         | 44144/569592 [11:45:04<449:59:45,  3.08s/it]
  8%|▊         | 44145/569592 [11:45:07<468:17:05,  3.21s/it]
                                                             

  8%|▊         | 44145/569592 [11:45:07<468:17:05,  3.21s/it]
  8%|▊         | 44146/569592 [11:45:08<376:00:23,  2.58s/it]
                                                             

  8%|▊         | 44146/569592 [11:45:08<376:00:23,  2.58s/it]
  8%|▊         | 44147/569592 [11:45:09<303:59:39,  2.08s/it]
                                                             

  8%|▊         | 44147/569592 [11:45:09<303:59:39,  2.08s/it]
  8%|▊         | 44148/569592 [11:45:13<370:04:04,  2.54s/it]
                                                             

  8%|▊         | 44148/569592 [11:45:13<370:04:04,  2.54s/it]
  8%|▊         | 44149/569592 [11:45:17<427:37:35,  2.93s/it]
                                                             

  8%|▊         | 44149/569592 [11:45:17<427:37:35,  2.93s/it]
  8%|▊         | 44150/569592 [11:45:20<439:15:14,  3.01s/it]
                                                             

  8%|▊         | 44150/569592 [11:45:20<439:15:14,  3.01s/it]
  8%|▊         | 44151/569592 [11:45:24<482:07:34,  3.30s/it]
                                                             

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  8%|▊       /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  8%|▊         | 44252/569592 [11:4/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95662272 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
9:59<474:47:16,  3.25s/it]
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                          /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (96631063 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                   

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                                                          /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90750000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
   

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  8%|�/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  8%|▊         | 44461/569592 [11:59:27<431:44:45,  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
2.96s/it]
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           /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (101647872 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                  

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                           /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (92243200 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                  

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  8%|▊         | 44569/569592 [/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
12:04:08<352:01:13,  2.41s/it]
                                                             

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  8%|▊         | 44654/569592 [12:07:49<464:03:38,  3/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (108000000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
.18s/it]
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  8%|▊         | 44670/569592 [12:08:36<422:29:28,  2.90s/it]
                                                             

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  8%|▊         | 44719/569592 [12:10:56<405:24:41,  2/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
.78s/it]
                                                             

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  8%|▊         | 44763/569592 [12:12:47<339:59:43,  2.33s/it]
  8%|▊         | 44764/569592 [12:12:49<306:26:15,  2.10s/it]
                                                             

  8%|▊         | 44764/569592 [12:12:49<306:26:15,  2.10s/it]
  8%|▊         | 44765/569592 [12:12:51<309:22:23,  2.12s/it]
                                                             

  8%|▊         | 44765/569592 [12:12:51<309:22:23,  2.12s/it]
  8%|▊         | 44766/569592 [12:12:54<364:33:33,  2.50s/it]
                                                             

  8%|▊         | 44766/569592 [12:12:54<364:33:33,  2.50s/it]
  8%|▊         | 44767/569592 [12:12:58<427:20:55,  2.93s/it]
                                                             

  8%|▊         | 44767/569592 [12:12:58<427:20:55,  2.93s/it]
  8%|▊         | 44768/569592 [12:13:00<381:24:15,  2.62s/it]
                                                             

  8%|▊         | 44768/569592 [12:13:00<381:24:15,  2.62s/it]
  8%|▊         | 44769/569592 [12:13:01<315:23:22,  2.16s/it]
                                                             

  8%|▊         | 44769/569592 [12:13:01<315:23:22,  2.16s/it]
  8%|▊         | 44770/569592 [12:13:05<392:03:01,  2.69s/it]
                                                             

  8%|▊         | 44770/569592 [12:13:05<392:03:01,  2.69s/it]
  8%|▊         | 44771/569592 [12:13:10<497:35:39,  3.41s/it]
                                                             

  8%|▊         | 44771/569592 [12:13:10<497:35:39,  3.41s/it]
  8%|▊         | 44772/569592 [12:13:14<498:56:58,  3.42s/it]
                                                             

  8%|▊         | 44772/569592 [12:13:14<498:56:58,  3.42s/it]
  8%|▊         | 44773/569592 [12:13:15<393:10:49,  2.70s/it]
                                                             

  8%|▊         | 44773/569592 [12:13:15<393:10:49,  2.70s/it]
  8%|▊         | 44774/569592 [12:13:18<417:42:33,  2.87s/it]
                                                             

  8%|▊         | 44774/569592 [12:13:18<417:42:33,  2.87s/it]
  8%|▊         | 44775/569592 [12:13:19<333:27:19,  2.29s/it]
                                                             

  8%|▊         | 44775/569592 [12:13:19<333:27:19,  2.29s/it]
  8%|▊         | 44776/569592 [12:13:22<381:46:41,  2.62s/it]
                                                             

  8%|▊         | 44776/569592 [12:13:22<381:46:41,  2.62s/it]
  8%|▊         | 44777/569592 [12:13:26<440:24:53,  3.02s/it]
                                                             

  8%|▊         | 44777/569592 [12:13:26<440:24:53,  3.02s/it]
  8%|▊         | 44778/569592 [12:13:29<456:32:47,  3.13s/it]
                                                             

  8%|▊         | 44778/569592 [12:13:29<456:32:47,  3.13s/it]
  8%|▊         | 44779/569592 [12:13:34<500:02:30,  3.43s/it]
                                                             

  8%|▊         | 44779/569592 [12:13:34<500:02:30,  3.43s/it]
  8%|▊         | 44780/569592 [12:13:37<502:44:13,  3.45s/it]
                                                             

  8%|▊         | 44780/569592 [12:13:37<502:44:13,  3.45s/it]
  8%|▊         | 44781/569592 [12:13:40<493:08:15,  3.38s/it]
                                                             

  8%|▊         | 44781/569592 [12:13:40<493:08:15,  3.38s/it]
  8%|▊         | 44782/569592 [12:13:44<498:22:28,  3.42s/it]
                                                             

  8%|▊         | 44782/569592 [12:13:44<498:22:28,  3.42s/it]
  8%|▊         | 44783/569592 [12:13:45<388:56:01,  2.67s/it]
                                                             

  8%|▊         | 44783/569592 [12:13:45<388:56:01,  2.67s/it]
  8%|▊         | 44784/569592 [12:13:48<425:40:43,  2.92s/it]
                                                             

  8%|▊         | 44784/569592 [12:13:48<425:40:43,  2.92s/it]
  8%|▊         | 44785/569592 [12:13:52<466:50:37,  3.20s/it]
                                                             

  8%|▊         | 44785/569592 [12:13:52<466:50:37,  3.20s/it]
  8%|▊         | 44786/569592 [12:13:53<369:16:53,  2.53s/it]
                                                             

  8%|▊         | 44786/569592 [12:13:53<369:16:53,  2.53s/it]
  8%|▊         | 44787/569592 [12:13:56<406:36:15,  2.79s/it]
                                                             

  8%|▊         | 44787/569592 [12:13:56<406:36:15,  2.79s/it]
  8%|▊         | 44788/569592 [12:14:00<439:17:46,  3.01s/it]
                                                             

  8%|▊         | 44788/569592 [12:14:00<439:17:46,  3.01s/it]
  8%|▊         | 44789/569592 [12:14:04<502:43:57,  3.45s/it]
                                                             

  8%|▊         | 44789/569592 [12:14:04<502:43:57,  3.45s/it]
  8%|▊         | 44790/569592 [12:14:08<495:18:14,  3.40s/it]
                                                             

  8%|▊         | 44790/569592 [12:14:08<495:18:14,  3.40s/it]
  8%|▊         | 44791/569592 [12:14:11<500:26:49,  3.43s/it]
                                                             

  8%|▊         | 44791/569592 [12:14:11<500:26:49,  3.43s/it]
  8%|▊         | 44792/569592 [12:14:12<389:32:14,  2.67s/it]
                                                             

  8%|▊         | 44792/569592 [12:14:12<389:32:14,  2.67s/it]
  8%|▊         | 44793/569592 [12:14:13<315:12:16,  2.16s/it]
                                                             

  8%|▊         | 44793/569592 [12:14:13<315:12:16,  2.16s/it]
  8%|▊         | 44794/569592 [12:14:17<397:11:28,  2.72s/it]
                                                             

  8%|▊         | 44794/569592 [12:14:17<397:11:28,  2.72s/it]
  8%|▊         | 44795/569592 [12:14:21<447:06:02,  3.07s/it]
                                                             

  8%|▊         | 44795/569592 [12:14:21<447:06:02,  3.07s/it]
  8%|▊         | 44796/569592 [12:14:24<461:41:02,  3.17s/it]
                                                             

  8%|▊         | 44796/569592 [12:14:24<461:41:02,  3.17s/it]
  8%|▊         | 44797/569592 [12:14:27<455:22:41,  3.12s/it]
                                                             

  8%|▊         | 44797/569592 [12:14:27<455:22:41,  3.12s/it]
  8%|▊         | 44798/569592 [12:14:32<525:19:25,  3.60s/it]
                                                             

  8%|▊         | 44798/569592 [12:14:32<525:19:25,  3.60s/it]
  8%|▊         | 44799/569592 [12:14:33<407:56:02,  2.80s/it]
                                                             

  8%|▊         | 44799/569592 [12:14:33<407:56:02,  2.80s/it]
  8%|▊         | 44800/569592 [12:14:37<435:35:23,  2.99s/it]
                                                             

  8%|▊         | 44800/569592 [12:14:37<435:35:23,  2.99s/it]
  8%|▊         | 44801/569592 [12:14:40<455:48:49,  3.13s/it]
                                                             

  8%|▊         | 44801/569592 [12:14:40<455:48:49,  3.13s/it]
  8%|▊         | 44802/569592 [12:14:45<526:18:07,  3.61s/it]
                                                             

  8%|▊         | 44802/569592 [12:14:45<526:18:07,  3.61s/it]
  8%|▊         | 44803/569592 [12:14:48<518:30:51,  3.56s/it]
                                                             

  8%|▊         | 44803/569592 [12:14:48<518:30:51,  3.56s/it]
  8%|▊         | 44804/569592 [12:14:49<401:21:37,  2.75s/it]
                                                             

  8%|▊         | 44804/569592 [12:14:49<401:21:37,  2.75s/it]
  8%|▊         | 44805/569592 [12:14:53<436:46:15,  3.00s/it]
                                                             

  8%|▊         | 44805/569592 [12:14:53<436:46:15,  3.00s/it]
  8%|▊         | 44806/569592 [12:14:53<345:56:13,  2.37s/it]
                                                             

  8%|▊         | 44806/569592 [12:14:53<345:56:13,  2.37s/it]
  8%|▊         | 44807/569592 [12:14:57<405:26:01,  2.78s/it]
                                                             

  8%|▊         | 44807/569592 [12:14:57<405:26:01,  2.78s/it]
  8%|▊         | 44808/569592 [12:15:01<427:57:52,  2.94s/it]
                                                             

  8%|▊         | 44808/569592 [12:15:01<427:57:52,  2.94s/it]
  8%|▊         | 44809/569592 [12:15:02<343:03:20,  2.35s/it]
                                                             

  8%|▊         | 44809/569592 [12:15:02<343:03:20,  2.35s/it]
  8%|▊         | 44810/569592 [12:15:05<390:05:35,  2.68s/it]
                                                             

  8%|▊         | 44810/569592 [12:15:05<390:05:35,  2.68s/it]
  8%|▊         | 44811/569592 [12:15:09<445:42:01,  3.06s/it]
                                                             

  8%|▊         | 44811/569592 [12:15:09<445:42:01,  3.06s/it]
  8%|▊         | 44812/569592 [12:15:10<353:18:16,  2.42s/it]
                                                             

  8%|▊         | 44812/569592 [12:15:10<353:18:16,  2.42s/it]
  8%|▊         | 44813/569592 [12:15:14<420:51:35,  2.89s/it]
                                                             

  8%|▊         | 44813/569592 [12:15:14<420:51:35,  2.89s/it]
  8%|▊         | 44814/569592 [12:15:15<336:00:13,  2.30s/it]
                                                             

  8%|▊         | 44814/569592 [12:15:15<336:00:13,  2.30s/it]
  8%|▊         | 44815/569592 [12:15:18<395:09:02,  2.71s/it]
                                                             

  8%|▊         | 44815/569592 [12:15:18<395:09:02,  2.71s/it]
  8%|▊         | 44816/569592 [12:15:22<429:27:22,  2.95s/it]
                                                             

  8%|▊         | 44816/569592 [12:15:22<429:27:22,  2.95s/it]
  8%|▊         | 44817/569592 [12:15:23<344:02:30,  2.36s/it]
                                                             

  8%|▊         | 44817/569592 [12:15:23<344:02:30,  2.36s/it]
  8%|▊         | 44818/569592 [12:15:27<411:23:46,  2.82s/it]
                                                             

  8%|▊         | 44818/569592 [12:15:27<411:23:46,  2.82s/it]
  8%|▊         | 44819/569592 [12:15:28<329:38:25,  2.26s/it]
                                                             

  8%|▊         | 44819/569592 [12:15:28<329:38:25,  2.26s/it]
  8%|▊         | 44820/569592 [12:15:29<272:36:46,  1.87s/it]
                                                             

  8%|▊         | 44820/569592 [12:15:29<272:36:46,  1.87s/it]
  8%|▊         | 44821/569592 [12:15:32<351:00:50,  2.41s/it]
                                                             

  8%|▊         | 44821/569592 [12:15:32<351:00:50,  2.41s/it]
  8%|▊         | 44822/569592 [12:15:33<288:51:18,  1.98s/it]
                                                             

  8%|▊         | 44822/569592 [12:15:33<288:51:18,  1.98s/it]
  8%|▊         | 44823/569592 [12:15:37<378:46:16,  2.60s/it]
                                                             

  8%|▊         | 44823/569592 [12:15:37<378:46:16,  2.60s/it]
  8%|▊         | 44824/569592 [12:15:41<409:16:50,  2.81s/it]
                                                             

  8%|▊         | 44824/569592 [12:15:41<409:16:50,  2.81s/it]
  8%|▊         | 44825/569592 [12:15:45<456:38:47,  3.13s/it]
                                                             

  8%|▊         | 44825/569592 [12:15:45<456:38:47,  3.13s/it]
  8%|▊         | 44826/569592 [12:15:48<487:05:32,  3.34s/it]
                                                             

  8%|▊         | 44826/569592 [12:15:48<487:05:32,  3.34s/it]
  8%|▊         | 44827/569592 [12:15:52<477:14:40,  3.27s/it]
                                                             

  8%|▊         | 44827/569592 [12:15:52<477:14:40,  3.27s/it]
  8%|▊         | 44828/569592 [12:15:55<493:59:09,  3.39s/it]
                                                             

  8%|▊         | 44828/569592 [12:15:55<493:59:09,  3.39s/it]
  8%|▊         | 44829/569592 [12:15:58<487:40:27,  3.35s/it]
                                                             

  8%|▊         | 44829/569592 [12:15:58<487:40:27,  3.35s/it]
  8%|▊         | 44830/569592 [12:15:59<380:41:07,  2.61s/it]
                                                             

  8%|▊         | 44830/569592 [12:15:59<380:41:07,  2.61s/it]
  8%|▊         | 44831/569592 [12:16:04<452:23:17,  3.10s/it]
                                                             

  8%|▊         | 44831/569592 [12:16:04<452:23:17,  3.10s/it]
  8%|▊         | 44832/569592 [12:16:07<457:59:26,  3.14s/it]
                                                             

  8%|▊         | 44832/569592 [12:16:07<457:59:26,  3.14s/it]
  8%|▊         | 44833/569592 [12:16:08<362:17:46,  2.49s/it]
                                                             

  8%|▊         | 44833/569592 [12:16:08<362:17:46,  2.49s/it]
  8%|▊         | 44834/569592 [12:16:11<403:31:20,  2.77s/it]
                                                             

  8%|▊         | 44834/569592 [12:16:11<403:31:20,  2.77s/it]
  8%|▊         | 44835/569592 [12:16:15<450:34:04,  3.09s/it]
                                                             

  8%|▊         | 44835/569592 [12:16:15<450:34:04,  3.09s/it]
  8%|▊         | 44836/569592 [12:16:16<358:34:04,  2.46s/it]
                                                             

  8%|▊         | 44836/569592 [12:16:16<358:34:04,  2.46s/it]
  8%|▊         | 44837/569592 [12:16:20<405:46:57,  2.78s/it]
                                                             

  8%|▊         | 44837/569592 [12:16:20<405:46:57,  2.78s/it]
  8%|▊         | 44838/569592 [12:16:23<435:26:52,  2.99s/it]
                                                             

  8%|▊         | 44838/569592 [12:16:23<435:26:52,  2.99s/it]
  8%|▊         | 44839/569592 [12:16:27<471:09:39,  3.23s/it]
                                                             

  8%|▊         | 44839/569592 [12:16:27<471:09:39,  3.23s/it]
  8%|▊         | 44840/569592 [12:16:30<480:27:07,  3.30s/it]
                                                             

  8%|▊         | 44840/569592 [12:16:30<480:27:07,  3.30s/it]
  8%|▊         | 44841/569592 [12:16:31<377:10:54,  2.59s/it]
                                                             

  8%|▊         | 44841/569592 [12:16:31<377:10:54,  2.59s/it]
  8%|▊         | 44842/569592 [12:16:32<304:36:25,  2.09s/it]
                                                             

  8%|▊         | 44842/569592 [12:16:32<304:36:25,  2.09s/it]
  8%|▊         | 44843/569592 [12:16:36<367:56:56,  2.52s/it]
                                                             

  8%|▊         | 44843/569592 [12:16:36<367:56:56,  2.52s/it]
  8%|▊         | 44844/569592 [12:16:37<302:38:28,  2.08s/it]
                                                             

  8%|▊         | 44844/569592 [12:16:37<302:38:28,  2.08s/it]
  8%|▊         | 44845/569592 [12:16:40<369:57:28,  2.54s/it]
                                                             

  8%|▊         | 44845/569592 [12:16:40<369:57:28,  2.54s/it]
  8%|▊         | 44846/569592 [12:16:41<302:39:35,  2.08s/it]
                                                             

  8%|▊         | 44846/569592 [12:16:41<302:39:35,  2.08s/it]
  8%|▊         | 44847/569592 [12:16:45<376:05:15,  2.58s/it]
                                                             

  8%|▊         | 44847/569592 [12:16:45<376:05:15,  2.58s/it]
  8%|▊         | 44848/569592 [12:16:46<307:33:18,  2.11s/it]
                                                             

  8%|▊         | 44848/569592 [12:16:46<307:33:18,  2.11s/it]
  8%|▊         | 44849/569592 [12:16:50<382:30:37,  2.62s/it]
                                                             

  8%|▊         | 44849/569592 [12:16:50<382:30:37,  2.62s/it]
  8%|▊         | 44850/569592 [12:16:51<310:30:15,  2.13s/it]
                                                             

  8%|▊         | 44850/569592 [12:16:51<310:30:15,  2.13s/it]
  8%|▊         | 44851/569592 [12:16:55<376:49:44,  2.59s/it]
                                                             

  8%|▊         | 44851/569592 [12:16:55<376:49:44,  2.59s/it]
  8%|▊         | 44852/569592 [12:16:58<428:18:00,  2.94s/it]
                                                             

  8%|▊         | 44852/569592 [12:16:58<428:18:00,  2.94s/it]
  8%|▊         | 44853/569592 [12:17:02<442:47:16,  3.04s/it]
                                                             

  8%|▊         | 44853/569592 [12:17:02<442:47:16,  3.04s/it]
  8%|▊         | 44854/569592 [12:17:05<455:04:50,  3.12s/it]
                                                             

  8%|▊         | 44854/569592 [12:17:05<455:04:50,  3.12s/it]
  8%|▊         | 44855/569592 [12:17:08<465:42:51,  3.20s/it]
                                                             

  8%|▊         | 44855/569592 [12:17:08<465:42:51,  3.20s/it]
  8%|▊         | 44856/569592 [12:17:12<478:38:25,  3.28s/it]
                                                             

  8%|▊         | 44856/569592 [12:17:12<478:38:25,  3.28s/it]
  8%|▊         | 44857/569592 [12:17:15<490:03:44,  3.36s/it]
                                                             

  8%|▊         | 44857/569592 [12:17:15<490:03:44,  3.36s/it]
  8%|▊         | 44858/569592 [12:17:19<489:29:58,  3.36s/it]
                                                             

  8%|▊         | 44858/569592 [12:17:19<489:29:58,  3.36s/it]
  8%|▊         | 44859/569592 [12:17:20<382:29:03,  2.62s/it]
                                                             

  8%|▊         | 44859/569592 [12:17:20<382:29:03,  2.62s/it]
  8%|▊         | 44860/569592 [12:17:20<308:51:32,  2.12s/it]
                                                             

  8%|▊         | 44860/569592 [12:17:21<308:51:32,  2.12s/it]
  8%|▊         | 44861/569592 [12:17:25<393:23:17,  2.70s/it]
                                                             

  8%|▊         | 44861/569592 [12:17:25<393:23:17,  2.70s/it]
  8%|▊         | 44862/569592 [12:17:25<316:53:07,  2.17s/it]
                                                             

  8%|▊         | 44862/569592 [12:17:25<316:53:07,  2.17s/it]
  8%|▊         | 44863/569592 [12:17:26<263:31:38,  1.81s/it]
                                                             

  8%|▊         | 44863/569592 [12:17:26<263:31:38,  1.81s/it]
  8%|▊         | 44864/569592 [12:17:27<225:39:49,  1.55s/it]
                                                             

  8%|▊         | 44864/569592 [12:17:27<225:39:49,  1.55s/it]
  8%|▊         | 44865/569592 [12:17:28<198:40:59,  1.36s/it]
                                                             

  8%|▊         | 44865/569592 [12:17:28<198:40:59,  1.36s/it]
  8%|▊         | 44866/569592 [12:17:32<288:58:56,  1.98s/it]
                                                             

  8%|▊         | 44866/569592 [12:17:32<288:58:56,  1.98s/it]
  8%|▊         | 44867/569592 [12:17:35<355:25:46,  2.44s/it]
                                                             

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  8%|▊         | /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (94148209 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  8%|▊         | 45000/569592 [12:23:30<298:38:53,  2.05s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-45000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-45000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-45000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-45000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-45000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-45000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-44000] due to args.save_total_limit

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  warnings.warn(
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  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100663296 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (119245980 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  8%|▊         | 45140/569592 [12:32:11<482:05:16,  3/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90936000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
.31s/it]
                                                             

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  8%|▊         |/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (97518456 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 45167/569592 [12:33:24<421:10:33,  2.89s/it]
                                                             

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                  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (93246930 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                           

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        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95727954 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                     

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                        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                     

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                                                        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
     

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         /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (92302080 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                    

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  8%|▊         | 45563/569592/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (96806588 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 [12:51:22<525:40:53,  3.61s/it]
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  8%|▊  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98911692 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
       | 45606/569592 [12:53:28<459:02:10,  3.15s/it]
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  8%|▊         | 45638/569592 [12:55:02</home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
361:58:22,  2.49s/it]
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  8%|▊         | 45661/569592 [12:55:55<345:19:29,  2.37s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98155200 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

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  8%|▊         | 45679/569592 [12:56:42<360:14:18,  2.48s/it]
  8%|▊         | 45680/569592 [12:56:44<338:23:21,  2.33s/it]
                                                             

  8%|▊         | 45680/569592 [12:56:44<338:23:21,  2.33s/it]
  8%|▊         | 45681/569592 [12:56:48<405:07:43,  2.78s/it]
                                                             

  8%|▊         | 45681/569592 [12:56:48<405:07:43,  2.78s/it]
  8%|▊         | 45682/569592 [12:56:52<441:08:23,  3.03s/it]
                                                             

  8%|▊         | 45682/569592 [12:56:52<441:08:23,  3.03s/it]
  8%|▊         | 45683/569592 [12:56:53<352:45:58,  2.42s/it]
                                                             

  8%|▊         | 45683/569592 [12:56:53<352:45:58,  2.42s/it]
  8%|▊         | 45684/569592 [12:56:57<443:48:09,  3.05s/it]
                                                             

  8%|▊         | 45684/569592 [12:56:57<443:48:09,  3.05s/it]
  8%|▊         | 45685/569592 [12:56:58<351:25:34,  2.41s/it]
                                                             

  8%|▊         | 45685/569592 [12:56:58<351:25:34,  2.41s/it]
  8%|▊         | 45686/569592 [12:57:02<394:37:39,  2.71s/it]
                                                             

  8%|▊         | 45686/569592 [12:57:02<394:37:39,  2.71s/it]
  8%|▊         | 45687/569592 [12:57:05<440:54:02,  3.03s/it]
                                                             

  8%|▊         | 45687/569592 [12:57:05<440:54:02,  3.03s/it]
  8%|▊         | 45688/569592 [12:57:09<450:53:39,  3.10s/it]
                                                             

  8%|▊         | 45688/569592 [12:57:09<450:53:39,  3.10s/it]
  8%|▊         | 45689/569592 [12:57:12<456:55:40,  3.14s/it]
                                                             

  8%|▊         | 45689/569592 [12:57:12<456:55:40,  3.14s/it]
  8%|▊         | 45690/569592 [12:57:16<482:10:42,  3.31s/it]
                                                             

  8%|▊         | 45690/569592 [12:57:16<482:10:42,  3.31s/it]
  8%|▊         | 45691/569592 [12:57:17<377:56:38,  2.60s/it]
                                                             

  8%|▊         | 45691/569592 [12:57:17<377:56:38,  2.60s/it]
  8%|▊         | 45692/569592 [12:57:20<428:27:42,  2.94s/it]
                                                             

  8%|▊         | 45692/569592 [12:57:20<428:27:42,  2.94s/it]
  8%|▊         | 45693/569592 [12:57:21<339:52:13,  2.34s/it]
                                                             

  8%|▊         | 45693/569592 [12:57:21<339:52:13,  2.34s/it]
  8%|▊         | 45694/569592 [12:57:26<429:46:58,  2.95s/it]
                                                             

  8%|▊         | 45694/569592 [12:57:26<429:46:58,  2.95s/it]
  8%|▊         | 45695/569592 [12:57:27<341:27:49,  2.35s/it]
                                                             

  8%|▊         | 45695/569592 [12:57:27<341:27:49,  2.35s/it]
  8%|▊         | 45696/569592 [12:57:30<400:00:00,  2.75s/it]
                                                             

  8%|▊         | 45696/569592 [12:57:30<400:00:00,  2.75s/it]
  8%|▊         | 45697/569592 [12:57:34<463:53:54,  3.19s/it]
                                                             

  8%|▊         | 45697/569592 [12:57:35<463:53:54,  3.19s/it]
  8%|▊         | 45698/569592 [12:57:35<369:11:39,  2.54s/it]
                                                             

  8%|▊         | 45698/569592 [12:57:36<369:11:39,  2.54s/it]
  8%|▊         | 45699/569592 [12:57:39<393:48:23,  2.71s/it]
                                                             

  8%|▊         | 45699/569592 [12:57:39<393:48:23,  2.71s/it]
  8%|▊         | 45700/569592 [12:57:42<411:50:48,  2.83s/it]
                                                             

  8%|▊         | 45700/569592 [12:57:42<411:50:48,  2.83s/it]
  8%|▊         | 45701/569592 [12:57:43<331:06:08,  2.28s/it]
                                                             

  8%|▊         | 45701/569592 [12:57:43<331:06:08,  2.28s/it]
  8%|▊         | 45702/569592 [12:57:46<373:42:11,  2.57s/it]
                                                             

  8%|▊         | 45702/569592 [12:57:46<373:42:11,  2.57s/it]
  8%|▊         | 45703/569592 [12:57:47<303:33:14,  2.09s/it]
                                                             

  8%|▊         | 45703/569592 [12:57:47<303:33:14,  2.09s/it]
  8%|▊         | 45704/569592 [12:57:48<253:46:11,  1.74s/it]
                                                             

  8%|▊         | 45704/569592 [12:57:48<253:46:11,  1.74s/it]
  8%|▊         | 45705/569592 [12:57:51<327:31:30,  2.25s/it]
                                                             

  8%|▊         | 45705/569592 [12:57:51<327:31:30,  2.25s/it]
  8%|▊         | 45706/569592 [12:57:56<427:57:01,  2.94s/it]
                                                             

  8%|▊         | 45706/569592 [12:57:56<427:57:01,  2.94s/it]
  8%|▊         | 45707/569592 [12:57:57<340:00:19,  2.34s/it]
                                                             

  8%|▊         | 45707/569592 [12:57:57<340:00:19,  2.34s/it]
  8%|▊         | 45708/569592 [12:58:01<407:03:37,  2.80s/it]
                                                             

  8%|▊         | 45708/569592 [12:58:01<407:03:37,  2.80s/it]
  8%|▊         | 45709/569592 [12:58:04<442:52:11,  3.04s/it]
                                                             

  8%|▊         | 45709/569592 [12:58:04<442:52:11,  3.04s/it]
  8%|▊         | 45710/569592 [12:58:05<355:25:11,  2.44s/it]
                                                             

  8%|▊         | 45710/569592 [12:58:05<355:25:11,  2.44s/it]
  8%|▊         | 45711/569592 [12:58:06<291:44:41,  2.00s/it]
                                                             

  8%|▊         | 45711/569592 [12:58:06<291:44:41,  2.00s/it]
  8%|▊         | 45712/569592 [12:58:10<348:51:05,  2.40s/it]
                                                             

  8%|▊         | 45712/569592 [12:58:10<348:51:05,  2.40s/it]
  8%|▊         | 45713/569592 [12:58:13<412:07:49,  2.83s/it]
                                                             

  8%|▊         | 45713/569592 [12:58:13<412:07:49,  2.83s/it]
  8%|▊         | 45714/569592 [12:58:17<446:03:47,  3.07s/it]
                                                             

  8%|▊         | 45714/569592 [12:58:17<446:03:47,  3.07s/it]
  8%|▊         | 45715/569592 [12:58:21<478:05:32,  3.29s/it]
                                                             

  8%|▊         | 45715/569592 [12:58:21<478:05:32,  3.29s/it]
  8%|▊         | 45716/569592 [12:58:24<482:36:26,  3.32s/it]
                                                             

  8%|▊         | 45716/569592 [12:58:24<482:36:26,  3.32s/it]
  8%|▊         | 45717/569592 [12:58:28<493:29:53,  3.39s/it]
                                                             

  8%|▊         | 45717/569592 [12:58:28<493:29:53,  3.39s/it]
  8%|▊         | 45718/569592 [12:58:33<554:23:42,  3.81s/it]
                                                             

  8%|▊         | 45718/569592 [12:58:33<554:23:42,  3.81s/it]
  8%|▊         | 45719/569592 [12:58:36<517:46:13,  3.56s/it]
                                                             

  8%|▊         | 45719/569592 [12:58:36<517:46:13,  3.56s/it]
  8%|▊         | 45720/569592 [12:58:36<400:51:30,  2.75s/it]
                                                             

  8%|▊         | 45720/569592 [12:58:36<400:51:30,  2.75s/it]
  8%|▊         | 45721/569592 [12:58:40<443:49:05,  3.05s/it]
                                                             

  8%|▊         | 45721/569592 [12:58:40<443:49:05,  3.05s/it]
  8%|▊         | 45722/569592 [12:58:44<466:39:34,  3.21s/it]
                                                             

  8%|▊         | 45722/569592 [12:58:44<466:39:34,  3.21s/it]
  8%|▊         | 45723/569592 [12:58:47<474:39:26,  3.26s/it]
                                                             

  8%|▊         | 45723/569592 [12:58:47<474:39:26,  3.26s/it]
  8%|▊         | 45724/569592 [12:58:50<469:45:07,  3.23s/it]
                                                             

  8%|▊         | 45724/569592 [12:58:50<469:45:07,  3.23s/it]
  8%|▊         | 45725/569592 [12:58:51<368:15:59,  2.53s/it]
                                                             

  8%|▊         | 45725/569592 [12:58:51<368:15:59,  2.53s/it]
  8%|▊         | 45726/569592 [12:58:55<407:52:31,  2.80s/it]
                                                             

  8%|▊         | 45726/569592 [12:58:55<407:52:31,  2.80s/it]
  8%|▊         | 45727/569592 [12:58:58<437:23:48,  3.01s/it]
                                                             

  8%|▊         | 45727/569592 [12:58:58<437:23:48,  3.01s/it]
  8%|▊         | 45728/569592 [12:59:02<464:15:16,  3.19s/it]
                                                             

  8%|▊         | 45728/569592 [12:59:02<464:15:16,  3.19s/it]
  8%|▊         | 45729/569592 [12:59:06<500:07:07,  3.44s/it]
                                                             

  8%|▊         | 45729/569592 [12:59:06<500:07:07,  3.44s/it]
  8%|▊         | 45730/569592 [12:59:09<487:31:40,  3.35s/it]
                                                             

  8%|▊         | 45730/569592 [12:59:09<487:31:40,  3.35s/it]
  8%|▊         | 45731/569592 [12:59:13<509:08:36,  3.50s/it]
                                                             

  8%|▊         | 45731/569592 [12:59:13<509:08:36,  3.50s/it]
  8%|▊         | 45732/569592 [12:59:16<502:56:40,  3.46s/it]
                                                             

  8%|▊         | 45732/569592 [12:59:16<502:56:40,  3.46s/it]
  8%|▊         | 45733/569592 [12:59:20<507:06:44,  3.48s/it]
                                                             

  8%|▊         | 45733/569592 [12:59:20<507:06:44,  3.48s/it]
  8%|▊         | 45734/569592 [12:59:23<501:33:31,  3.45s/it]
                                                             

  8%|▊         | 45734/569592 [12:59:23<501:33:31,  3.45s/it]
  8%|▊         | 45735/569592 [12:59:24<390:20:04,  2.68s/it]
                                                             

  8%|▊         | 45735/569592 [12:59:24<390:20:04,  2.68s/it]
  8%|▊         | 45736/569592 [12:59:27<422:10:48,  2.90s/it]
                                                             

  8%|▊         | 45736/569592 [12:59:27<422:10:48,  2.90s/it]
  8%|▊         | 45737/569592 [12:59:31<436:59:01,  3.00s/it]
                                                             

  8%|▊         | 45737/569592 [12:59:31<436:59:01,  3.00s/it]
  8%|▊         | 45738/569592 [12:59:34<475:06:11,  3.26s/it]
                                                             

  8%|▊         | 45738/569592 [12:59:34<475:06:11,  3.26s/it]
  8%|▊         | 45739/569592 [12:59:35<371:59:17,  2.56s/it]
                                                             

  8%|▊         | 45739/569592 [12:59:35<371:59:17,  2.56s/it]
  8%|▊         | 45740/569592 [12:59:39<423:37:59,  2.91s/it]
                                                             

  8%|▊         | 45740/569592 [12:59:39<423:37:59,  2.91s/it]
  8%|▊         | 45741/569592 [12:59:40<336:34:29,  2.31s/it]
                                                             

  8%|▊         | 45741/569592 [12:59:40<336:34:29,  2.31s/it]
  8%|▊         | 45742/569592 [12:59:44<407:54:42,  2.80s/it]
                                                             

  8%|▊         | 45742/569592 [12:59:44<407:54:42,  2.80s/it]
  8%|▊         | 45743/569592 [12:59:45<327:05:56,  2.25s/it]
                                                             

  8%|▊         | 45743/569592 [12:59:45<327:05:56,  2.25s/it]
  8%|▊         | 45744/569592 [12:59:49<399:44:36,  2.75s/it]
                                                             

  8%|▊         | 45744/569592 [12:59:49<399:44:36,  2.75s/it]
  8%|▊         | 45745/569592 [12:59:52<422:13:27,  2.90s/it]
                                                             

  8%|▊         | 45745/569592 [12:59:52<422:13:27,  2.90s/it]
  8%|▊         | 45746/569592 [12:59:53<336:31:43,  2.31s/it]
                                                             

  8%|▊         | 45746/569592 [12:59:53<336:31:43,  2.31s/it]
  8%|▊         | 45747/569592 [12:59:57<414:02:57,  2.85s/it]
                                                             

  8%|▊         | 45747/569592 [12:59:57<414:02:57,  2.85s/it]
  8%|▊         | 45748/569592 [13:00:01<453:24:38,  3.12s/it]
                                                             

  8%|▊         | 45748/569592 [13:00:01<453:24:38,  3.12s/it]
  8%|▊         | 45749/569592 [13:00:04<455:22:28,  3.13s/it]
                                                             

  8%|▊         | 45749/569592 [13:00:04<455:22:28,  3.13s/it]
  8%|▊         | 45750/569592 [13:00:08<495:48:05,  3.41s/it]
                                                             

  8%|▊         | 45750/569592 [13:00:08<495:48:05,  3.41s/it]
  8%|▊         | 45751/569592 [13:00:09<387:39:57,  2.66s/it]
                                                             

  8%|▊         | 45751/569592 [13:00:09<387:39:57,  2.66s/it]
  8%|▊         | 45752/569592 [13:00:13<453:30:28,  3.12s/it]
                                                             

  8%|▊         | 45752/569592 [13:00:13<453:30:28,  3.12s/it]
  8%|▊         | 45753/569592 [13:00:14<359:30:36,  2.47s/it]
                                                             

  8%|▊         | 45753/569592 [13:00:14<359:30:36,  2.47s/it]
  8%|▊         | 45754/569592 [13:00:15<294:05:07,  2.02s/it]
                                                             

  8%|▊         | 45754/569592 [13:00:15<294:05:07,  2.02s/it]
  8%|▊         | 45755/569592 [13:00:16<248:23:00,  1.71s/it]
                                                             

  8%|▊         | 45755/569592 [13:00:16<248:23:00,  1.71s/it]
  8%|▊         | 45756/569592 [13:00:20<326:23:22,  2.24s/it]
                                                             

  8%|▊         | 45756/569592 [13:00:20<326:23:22,  2.24s/it]
  8%|▊         | 45757/569592 [13:00:23<373:35:28,  2.57s/it]
                                                             

  8%|▊         | 45757/569592 [13:00:23<373:35:28,  2.57s/it]
  8%|▊         | 45758/569592 [13:00:28<489:14:52,  3.36s/it]
                                                             

  8%|▊         | 45758/569592 [13:00:28<489:14:52,  3.36s/it]
  8%|▊         | 45759/569592 [13:00:31<485:53:44,  3.34s/it]
                                                             

  8%|▊         | 45759/569592 [13:00:31<485:53:44,  3.34s/it]
  8%|▊         | 45760/569592 [13:00:34<473:21:28,  3.25s/it]
                                                             

  8%|▊         | 45760/569592 [13:00:34<473:21:28,  3.25s/it]
  8%|▊         | 45761/569592 [13:00:38<476:31:14,  3.27s/it]
                                                             

  8%|▊         | 45761/569592 [13:00:38<476:31:14,  3.27s/it]
  8%|▊         | 45762/569592 [13:00:39<373:06:48,  2.56s/it]
                                                             

  8%|▊         | 45762/569592 [13:00:39<373:06:48,  2.56s/it]
  8%|▊         | 45763/569592 [13:00:42<415:25:56,  2.86s/it]
                                                             

  8%|▊         | 45763/569592 [13:00:42<415:25:56,  2.86s/it]
  8%|▊         | 45764/569592 [13:00:43<334:41:40,  2.30s/it]
                                                             

  8%|▊         | 45764/569592 [13:00:43<334:41:40,  2.30s/it]
  8%|▊         | 45765/569592 [13:00:47<389:53:22,  2.68s/it]
                                                             

  8%|▊         | 45765/569592 [13:00:47<389:53:22,  2.68s/it]
  8%|▊         | 45766/569592 [13:00:51<457:09:41,  3.14s/it]
                                                             

  8%|▊         | 45766/569592 [13:00:51<457:09:41,  3.14s/it]
  8%|▊         | 45767/569592 [13:00:52<362:10:12,  2.49s/it]
                                                             

  8%|▊         | 45767/569592 [13:00:52<362:10:12,  2.49s/it]
  8%|▊         | 45768/569592 [13:00:56<418:54:59,  2.88s/it]
                                                             

  8%|▊         | 45768/569592 [13:00:56<418:54:59,  2.88s/it]
  8%|▊         | 45769/569592 [13:00:57<332:32:05,  2.29s/it]
                                                             

  8%|▊         | 45769/569592 [13:00:57<332:32:05,  2.29s/it]
  8%|▊         | 45770/569592 [13:00:58<275:06:39,  1.89s/it]
                                                             

  8%|▊         | 45770/569592 [13:00:58<275:06:39,  1.89s/it]
  8%|▊         | 45771/569592 [13:00:59<234:21:13,  1.61s/it]
                                                             

  8%|▊         | 45771/569592 [13:00:59<234:21:13,  1.61s/it]
  8%|▊         | 45772/569592 [13:01:00<204:35:29,  1.41s/it]
                                                             

  8%|▊         | 45772/569592 [13:01:00<204:35:29,  1.41s/it]
  8%|▊         | 45773/569592 [13:01:03<300:52:24,  2.07s/it]
                                                             

  8%|▊         | 45773/569592 [13:01:03<300:52:24,  2.07s/it]
  8%|▊         | 45774/569592 [13:01:06<355:41:18,  2.44s/it]
                                                             

  8%|▊         | 45774/569592 [13:01:06<355:41:18,  2.44s/it]
  8%|▊         | 45775/569592 [13:01:10<406:14:27,  2.79s/it]
                                                             

  8%|▊         | 45775/569592 [13:01:10<406:14:27,  2.79s/it]
  8%|▊         | 45776/569592 [13:01:14<438:41:29,  3.01s/it]
                                                             

  8%|▊         | 45776/569592 [13:01:14<438:41:29,  3.01s/it]
  8%|▊         | 45777/569592 [13:01:17<461:40:08,  3.17s/it]
                                                             

  8%|▊         | 45777/569592 [13:01:17<461:40:08,  3.17s/it]
  8%|▊         | 45778/569592 [13:01:20<464:06:38,  3.19s/it]
                                                             

  8%|▊         | 45778/569592 [13:01:20<464:06:38,  3.19s/it]
  8%|▊         | 45779/569592 [13:01:21<364:03:23,  2.50s/it]
                                                             

  8%|▊         | 45779/569592 [13:01:21<364:03:23,  2.50s/it]
  8%|▊         | 45780/569592 [13:01:25<402:04:59,  2.76s/it]
                                                             

  8%|▊         | 45780/569592 [13:01:25<402:04:59,  2.76s/it]
  8%|▊         | 45781/569592 [13:01:28<431:06:09,  2.96s/it]
                                                             

  8%|▊         | 45781/569592 [13:01:28<431:06:09,  2.96s/it]
  8%|▊         | 45782/569592 [13:01:29<343:44:39,  2.36s/it]
                                                             

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/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95660180 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  warnings.warn(
 2.15s/it]
                                                             

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                                                /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98911692 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
             

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  8%|▊         | 46000/569592 [13:11:35<391:18:12,  2.69s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-46000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-46000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-46000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-46000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-46000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-46000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-45000] due to args.save_total_limit

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  warnings.warn(
2:38:14,  2.84s/it]
                                                             

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  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (92251504 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  warnings.warn(
7,  2.67s/it]
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  8%|▊         | 46177/5695/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98911692 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
92 [13:21:46<523:51:58,  3.60s/it]
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  8%|▊         | 46199/569592 [13:22:52<407:33:29,  2.80s/it]
                                                             

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  8%|▊         | 46207/569592 [13:23:14<332:31:18,  2.29s/it]
                                                             

  8%|▊         | 46207/569592 [13:23:14<332:31:18,  2.29s/it]
  8%|▊         | 46208/569592 [13:23:17<393:49:28,  2.71s/it]
                                                             

  8%|▊         | 46208/569592 [13:23:18<393:49:28,  2.71s/it]
  8%|▊         | 46209/569592 [13:23:21<447:23:22,  3.08s/it]
                                                             

  8%|▊         | 46209/569592 [13:23:21<447:23:22,  3.08s/it]
  8%|▊         | 46210/569592 [13:23:25<474:42:25,  3.27s/it]
                                                             

  8%|▊         | 46210/569592 [13:23:25<474:42:25,  3.27s/it]
  8%|▊         | 46211/569592 [13:23:29<483:29:21,  3.33s/it]
                                                             

  8%|▊         | 46211/569592 [13:23:29<483:29:21,  3.33s/it]
  8%|▊         | 46212/569592 [13:23:32<472:52:50,  3.25s/it]
                                                             

  8%|▊         | 46212/569592 [13:23:32<472:52:50,  3.25s/it]
  8%|▊         | 46213/569592 [13:23:35<468:50:03,  3.22s/it]
                                                             

  8%|▊         | 46213/569592 [13:23:35<468:50:03,  3.22s/it]
  8%|▊         | 46214/569592 [13:23:36<366:51:42,  2.52s/it]
                                                             

  8%|▊         | 46214/569592 [13:23:36<366:51:42,  2.52s/it]
  8%|▊         | 46215/569592 [13:23:39<413:52:51,  2.85s/it]
                                                             

  8%|▊         | 46215/569592 [13:23:39<413:52:51,  2.85s/it]
  8%|▊         | 46216/569592 [13:23:40<331:22:01,  2.28s/it]
                                                             

  8%|▊         | 46216/569592 [13:23:40<331:22:01,  2.28s/it]
  8%|▊         | 46217/569592 [13:23:41<272:01:48,  1.87s/it]
                                                             

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  8%|▊         | 46218/569592 [13:23:43<248:15:05,  1.71s/it]
                                                             

  8%|▊         | 46218/569592 [13:23:43<248:15:05,  1.71s/it]
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  8%|▊         | 46219/569592 [13:23:44<218:17:14,  1.50s/it]
  8%|▊         | 46220/569592 [13:23:48<325:18:04,  2.24s/it]
                                                             

  8%|▊         | 46220/569592 [13:23:48<325:18:04,  2.24s/it]
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  8%|▊         | 46223/569592 [13:23:55<330:35:06,  2.27s/it]
  8%|▊         | 46224/569592 [13:23:56<272:25:10,  1.87s/it]
                                                             

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  8%|▊         | 46225/569592 [13:23:58<245:26:46,  1.69s/it]
  8%|▊         | 46226/569592 [13:23:59<216:28:42,  1.49s/it]
                                                             

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  8%|▊         | 46230/569592 [13:24:08<266:09:26,  1.83s/it]
                                                             

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  8%|▊         | 46232/569592 [13:24:15<384:16:35,  2.64s/it]
                                                             

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  8%|▊         | 46233/569592 [13:24:19<421:00:48,  2.90s/it]
                                                             

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  8%|▊         | 46280/569592 [13:26:25<311:44:54,  2.14s/it]
                                                             

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  8%|▊         | 46287/569592 [13:26:45<340:58:07,  2.35s/it]
                                                             

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  8%|▊         | 46288/569592 [13:26:48<395:48:40,  2.72s/it]
                                                             

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  8/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  8%|▊         | /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100711308 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  8%|▊         | 46410/569592 [13:32:25<513:49:03,  3.54s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

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  8%|▊       /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  8%|▊         | 46528/569592 [13:37:49<459:27:40, /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (104282552 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 3.16s/it]
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  8%|▊        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 | 46620/569592 [13:42:05<265:21:05,  1.83s/it]
                                                             

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  8%|▊         | 46630/56/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (105844200 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
9592 [13:42:33<393:42:46,  2.71s/it]
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  warnings.warn(
92:52:56,  2.02s/it]
                                                             

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  8%|▊         /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (104506584 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
| 46813/569592 [13:50:48<289:51:04,  2.00s/it]
                                                             

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                                                      /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
       

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  warnings.warn(
6:20:58,  3.01s/it]
                                                             

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  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (102480384 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  warnings.warn(
.31s/it]
                                                             

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  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  8%|▊         | 47000/569592 [13:59:20<450:48:43,  3.11s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-47000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-47000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-47000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-47000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-47000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-47000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-46000] due to args.save_total_limit

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  8%|▊         | 47049//home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100663296 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
569592 [14:03:52<436:25:38,  3.01s/it]
                                                             

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         /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (103838130 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                    

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  8%|▊         | 47150/569592 [14:08:48<445:52:15,  3.07s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

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  8%|▊         | 47242/5/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
69592 [14:12:57<488:09:02,  3.36s/it]
                                                             

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                               /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95360000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                              

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  warnings.warn(
:33,  2.98s/it]
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                                                          /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (108000000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (92918464 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
   

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  8%|▊         | 47370/56/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (101412842 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
9592 [14:18:49<264:40:44,  1.82s/it]
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  8%|▊         | 474/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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  8%|▊         /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90750000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
| 47488/569592 [14:24:17<362:11:07,  2.50s/it]
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  8%|▊         | 47504/569592 [/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (93943008 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
14:25:05<353:33:03,  2.44s/it]
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                      /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (89913188 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                       

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  warnings.warn(
51,  3.39s/it]
                                                             

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  8%|�/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
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                                                 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
            

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  8%|▊         | 4768/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
7/569592 [14:33:40<417:41:31,  2.88s/it]
                                                             

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                            /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100499280 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                 

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                                            /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (101412842 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                 

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  8%|▊     /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90750000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95609284 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
    | 47740/569592 [14:36:15<459:11:56,  3.17s/it]
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  8%|▊         | 47821/5695/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
92 [14:39:48<461:21:50,  3.18s/it]
                                                             

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                                                  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98911692 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
           

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        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (125164400 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                     

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                        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (89963048 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                     

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                                                        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (99256512 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (101105589 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
     

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  8%|▊         | 48000/569592 [14:48:06<372:30:53,  2.57s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-48000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-48000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-48000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-48000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-48000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-48000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-47000] due to args.save_total_limit

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  8%|▊       /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90326016 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
  | 48102/569592 [14:55:18<426:24:57,  2.94s/it]
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  8%|▊         | 48111/569592 [14:55:40<406:20:40,  2.81s/it]
                                                             

  8%|▊         | 48111/569592 [14:55:40<406:20:40,  2.81s/it]
  8%|▊         | 48112/569592 [14:55:41<326:30:43,  2.25s/it]
                                                             

  8%|▊         | 48112/569592 [14:55:41<326:30:43,  2.25s/it]
  8%|▊         | 48113/569592 [14:55:42<275:04:06,  1.90s/it]
                                                             

  8%|▊         | 48113/569592 [14:55:42<275:04:06,  1.90s/it]
  8%|▊         | 48114/569592 [14:55:46<372:39:26,  2.57s/it]
                                                             

  8%|▊         | 48114/569592 [14:55:46<372:39:26,  2.57s/it]
  8%|▊         | 48115/569592 [14:55:50<440:14:40,  3.04s/it]
                                                             

  8%|▊         | 48115/569592 [14:55:50<440:14:40,  3.04s/it]
  8%|▊         | 48116/569592 [14:55:51<349:57:05,  2.42s/it]
                                                             

  8%|▊         | 48116/569592 [14:55:51<349:57:05,  2.42s/it]
  8%|▊         | 48117/569592 [14:55:55<410:29:57,  2.83s/it]
                                                             

  8%|▊         | 48117/569592 [14:55:55<410:29:57,  2.83s/it]
  8%|▊         | 48118/569592 [14:55:56<329:44:34,  2.28s/it]
                                                             

  8%|▊         | 48118/569592/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 [14:55:56<329:44:34,  2.28s/it]
  8%|▊         | 48119/569592 [14:55:57<272:09:13,  1.88s/it]
                                                             

  8%|▊         | 48119/569592 [14:55:57<272:09:13,  1.88s/it]
  8%|▊         | 48120/569592 [14:56:00<343:03:24,  2.37s/it]
                                                             

  8%|▊         | 48120/569592 [14:56:00<343:03:24,  2.37s/it]
  8%|▊         | 48121/569592 [14:56:01<283:36:35,  1.96s/it]
                                                             

  8%|▊         | 48121/569592 [14:56:01<283:36:35,  1.96s/it]
  8%|▊         | 48122/569592 [14:56:05<366:57:29,  2.53s/it]
                                                             

  8%|▊         | 48122/569592 [14:56:05<366:57:29,  2.53s/it]
  8%|▊         | 48123/569592 [14:56:09<405:18:19,  2.80s/it]
                                                             

  8%|▊         | 48123/569592 [14:56:09<405:18:19,  2.80s/it]
  8%|▊         | 48124/569592 [14:56:12<429:00:13,  2.96s/it]
                                                             

  8%|▊         | 48124/569592 [14:56:12<429:00:13,  2.96s/it]
  8%|▊         | 48125/569592 [14:56:16<476:16:26,  3.29s/it]
                                                             

  8%|▊         | 48125/569592 [14:56:16<476:16:26,  3.29s/it]
  8%|▊         | 48126/569592 [14:56:19<471:25:11,  3.25s/it]
                                                             

  8%|▊         | 48126/569592 [14:56:19<471:25:11,  3.25s/it]
  8%|▊         | 48127/569592 [14:56:24<523:34:47,  3.61s/it]
                                                             

  8%|▊         | 48127/569592 [14:56:24<523:34:47,  3.61s/it]
  8%|▊         | 48128/569592 [14:56:27<509:29:38,  3.52s/it]
                                                             

  8%|▊         | 48128/569592 [14:56:27<509:29:38,  3.52s/it]
  8%|▊         | 48129/569592 [14:56:28<396:17:42,  2.74s/it]
                                                             

  8%|▊         | 48129/569592 [14:56:28<396:17:42,  2.74s/it]
  8%|▊         | 48130/569592 [14:56:31<431:17:27,  2.98s/it]
                                                             

  8%|▊         | 48130/569592 [14:56:31<431:17:27,  2.98s/it]
  8%|▊         | 48131/569592 [14:56:35<452:45:36,  3.13s/it]
                                                             

  8%|▊         | 48131/569592 [14:56:35<452:45:36,  3.13s/it]
  8%|▊         | 48132/569592 [14:56:38<467:30:36,  3.23s/it]
                                                             

  8%|▊         | 48132/569592 [14:56:38<467:30:36,  3.23s/it]
  8%|▊         | 48133/569592 [14:56:42<471:46:48,  3.26s/it]
                                                             

  8%|▊         | 48133/569592 [14:56:42<471:46:48,  3.26s/it]
  8%|▊         | 48134/569592 [14:56:45<485:35:29,  3.35s/it]
                                                             

  8%|▊         | 48134/569592 [14:56:45<485:35:29,  3.35s/it]
  8%|▊         | 48135/569592 [14:56:46<383:03:30,  2.64s/it]
                                                             

  8%|▊         | 48135/569592 [14:56:46<383:03:30,  2.64s/it]
  8%|▊         | 48136/569592 [14:56:47<309:41:06,  2.14s/it]
                                                             

  8%|▊         | 48136/569592 [14:56:47<309:41:06,  2.14s/it]
  8%|▊         | 48137/569592 [14:56:48<270:52:32,  1.87s/it]
                                                             

  8%|▊         | 48137/569592 [14:56:48<270:52:32,  1.87s/it]
  8%|▊         | 48138/569592 [14:56:49<232:37:05,  1.61s/it]
                                                             

  8%|▊         | 48138/569592 [14:56:49<232:37:05,  1.61s/it]
  8%|▊         | 48139/569592 [14:56:50<203:12:45,  1.40s/it]
                                                             

  8%|▊         | 48139/569592 [14:56:50<203:12:45,  1.40s/it]
  8%|▊         | 48140/569592 [14:56:51<185:00:19,  1.28s/it]
                                                             

  8%|▊         | 48140/569592 [14:56:51<185:00:19,  1.28s/it]
  8%|▊         | 48141/569592 [14:56:55<290:54:39,  2.01s/it]
                                                             

  8%|▊         | 48141/569592 [14:56:55<290:54:39,  2.01s/it]
  8%|▊         | 48142/569592 [14:56:59<370:26:36,  2.56s/it]
                                                             

  8%|▊         | 48142/569592 [14:56:59<370:26:36,  2.56s/it]
  8%|▊         | 48143/569592 [14:57:03<421:54:11,  2.91s/it]
                                                             

  8%|▊         | 48143/569592 [14:57:03<421:54:11,  2.91s/it]
  8%|▊         | 48144/569592 [14:57:04<337:50:47,  2.33s/it]
                                                             

  8%|▊         | 48144/569592 [14:57:04<337:50:47,  2.33s/it]
  8%|▊         | 48145/569592 [14:57:08<415:56:22,  2.87s/it]
                                                             

  8%|▊         | 48145/569592 [14:57:08<415:56:22,  2.87s/it]
  8%|▊         | 48146/569592 [14:57:11<450:46:34,  3.11s/it]
                                                             

  8%|▊         | 48146/569592 [14:57:11<450:46:34,  3.11s/it]
  8%|▊         | 48147/569592 [14:57:12<357:40:23,  2.47s/it]
                                                             

  8%|▊         | 48147/569592 [14:57:12<357:40:23,  2.47s/it]
  8%|▊         | 48148/569592 [14:57:16<420:43:02,  2.90s/it]
                                                             

  8%|▊         | 48148/569592 [14:57:16<420:43:02,  2.90s/it]
  8%|▊         | 48149/569592 [14:57:20<440:28:25,  3.04s/it]
                                                             

  8%|▊         | 48149/569592 [14:57:20<440:28:25,  3.04s/it]
  8%|▊         | 48150/569592 [14:57:24<480:29:49,  3.32s/it]
                                                             

  8%|▊         | 48150/569592 [14:57:24<480:29:49,  3.32s/it]
  8%|▊         | 48151/569592 [14:57:27<481:31:20,  3.32s/it]
                                                             

  8%|▊         | 48151/569592 [14:57:27<481:31:20,  3.32s/it]
  8%|▊         | 48152/569592 [14:57:31<503:07:58,  3.47s/it]
                                                             

  8%|▊         | 48152/569592 [14:57:31<503:07:58,  3.47s/it]
  8%|▊         | 48153/569592 [14:57:34<497:57:55,  3.44s/it]
                                                             

  8%|▊         | 48153/569592 [14:57:34<497:57:55,  3.44s/it]
  8%|▊         | 48154/569592 [14:57:37<490:42:18,  3.39s/it]
                                                             

  8%|▊         | 48154/569592 [14:57:37<490:42:18,  3.39s/it]
  8%|▊         | 48155/569592 [14:57:41<494:13:20,  3.41s/it]
                                                             

  8%|▊         | 48155/569592 [14:57:41<494:13:20,  3.41s/it]
  8%|▊         | 48156/569592 [14:57:42<385:14:28,  2.66s/it]
    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (94040804 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                         

  8%|▊         | 48156/569592 [14:57:42<385:14:28,  2.66s/it]
  8%|▊         | 48157/569592 [14:57:46<447:01:38,  3.09s/it]
                                                             

  8%|▊         | 48157/569592 [14:57:46<447:01:38,  3.09s/it]
  8%|▊         | 48158/569592 [14:57:47<354:34:35,  2.45s/it]
                                                             

  8%|▊         | 48158/569592 [14:57:47<354:34:35,  2.45s/it]
  8%|▊         | 48159/569592 [14:57:48<290:28:27,  2.01s/it]
                                                             

  8%|▊         | 48159/569592 [14:57:48<290:28:27,  2.01s/it]
  8%|▊         | 48160/569592 [14:57:51<354:02:47,  2.44s/it]
                                                             

  8%|▊         | 48160/569592 [14:57:51<354:02:47,  2.44s/it]
  8%|▊         | 48161/569592 [14:57:55<414:17:48,  2.86s/it]
                                                             

  8%|▊  slurmstepd: error: *** JOB 338184 ON h100-st-p548xlarge-174 CANCELLED AT 2025-02-19T17:07:23 DUE TO JOB REQUEUE ***
       | 48161/569592 [14:57:55<414:17:48,  2.86s/it]
  8%|▊         | 48162/569592 [14:57:58<429:59:13,  2.97s/it]
                                                             

  8%|▊         | 48162/569592 [14:57:58<429:59:13,  2.97s/it]
  8%|▊         | 48163/569592 [14:58:02<452:53:52,  3.13s/it]
                                                             

  8%|▊         | 48163/569592 [14:58:02<452:53:52,  3.13s/it]slurmstepd: error: *** STEP 338184.0 ON h100-st-p548xlarge-174 CANCELLED AT 2025-02-19T17:07:23 DUE TO JOB REQUEUE ***
srun: Job step aborted: Waiting up to 32 seconds for job step to finish.
W0219 17:07:23.852000 2033589 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0219 17:07:23.852000 1986836 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0219 17:07:23.851000 2110507 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0219 17:07:23.852000 1983947 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0219 17:07:23.852000 1988962 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0219 17:07:23.852000 1986959 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0219 17:07:23.852000 1985034 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0219 17:07:23.853000 1985442 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0219 17:07:23.852000 1983838 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0219 17:07:23.851000 1990262 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0219 17:07:23.852000 1982123 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0219 17:07:23.852000 1987887 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0219 17:07:23.852000 1987087 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0219 17:07:23.853000 661040 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0219 17:07:23.852000 651329 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0219 17:07:23.859000 2110507 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2110633 closing signal SIGTERM
W0219 17:07:23.859000 1986836 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987616 closing signal SIGTERM
W0219 17:07:23.859000 2033589 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2033744 closing signal SIGTERM
W0219 17:07:23.859000 1983947 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1984424 closing signal SIGTERM
W0219 17:07:23.859000 1988962 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1989692 closing signal SIGTERM
W0219 17:07:23.859000 1986959 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987089 closing signal SIGTERM
W0219 17:07:23.861000 2110507 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2110634 closing signal SIGTERM
W0219 17:07:23.860000 1985034 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1985778 closing signal SIGTERM
W0219 17:07:23.861000 1983947 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1984425 closing signal SIGTERM
W0219 17:07:23.861000 1988962 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1989693 closing signal SIGTERM
W0219 17:07:23.861000 1986836 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987617 closing signal SIGTERM
W0219 17:07:23.861000 1986959 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987090 closing signal SIGTERM
W0219 17:07:23.860000 1983838 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1984028 closing signal SIGTERM
W0219 17:07:23.861000 2033589 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2033745 closing signal SIGTERM
W0219 17:07:23.860000 1985442 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1986205 closing signal SIGTERM
W0219 17:07:23.860000 1990262 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1990957 closing signal SIGTERM
W0219 17:07:23.860000 1982123 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1982250 closing signal SIGTERM
W0219 17:07:23.860000 1987887 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1988018 closing signal SIGTERM
W0219 17:07:23.861000 1985034 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1985779 closing signal SIGTERM
W0219 17:07:23.860000 1987087 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987848 closing signal SIGTERM
W0219 17:07:23.862000 1983838 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1984029 closing signal SIGTERM
W0219 17:07:23.862000 1983947 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1984426 closing signal SIGTERM
W0219 17:07:23.860000 661040 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 661163 closing signal SIGTERM
W0219 17:07:23.862000 1990262 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1990958 closing signal SIGTERM
W0219 17:07:23.862000 1985442 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1986206 closing signal SIGTERM
W0219 17:07:23.862000 1982123 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1982251 closing signal SIGTERM
W0219 17:07:23.862000 1987887 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1988019 closing signal SIGTERM
W0219 17:07:23.860000 651329 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 651748 closing signal SIGTERM
W0219 17:07:23.862000 1987087 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987849 closing signal SIGTERM
W0219 17:07:23.862000 1986836 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987618 closing signal SIGTERM
W0219 17:07:23.862000 661040 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 661164 closing signal SIGTERM
W0219 17:07:23.862000 1988962 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1989694 closing signal SIGTERM
W0219 17:07:23.862000 1983838 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1984030 closing signal SIGTERM
W0219 17:07:23.862000 2110507 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2110635 closing signal SIGTERM
W0219 17:07:23.862000 1990262 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1990959 closing signal SIGTERM
W0219 17:07:23.863000 2033589 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2033746 closing signal SIGTERM
W0219 17:07:23.863000 1986959 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987091 closing signal SIGTERM
W0219 17:07:23.863000 1985442 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1986207 closing signal SIGTERM
W0219 17:07:23.863000 1985034 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1985780 closing signal SIGTERM
W0219 17:07:23.863000 661040 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 661165 closing signal SIGTERM
W0219 17:07:23.863000 1987887 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1988020 closing signal SIGTERM
W0219 17:07:23.863000 1988962 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1989695 closing signal SIGTERM
W0219 17:07:23.863000 1982123 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1982252 closing signal SIGTERM
W0219 17:07:23.863000 1986959 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987092 closing signal SIGTERM
W0219 17:07:23.864000 1982123 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1982253 closing signal SIGTERM
W0219 17:07:23.864000 2033589 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2033747 closing signal SIGTERM
W0219 17:07:23.864000 1987087 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987850 closing signal SIGTERM
W0219 17:07:23.864000 1983947 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1984427 closing signal SIGTERM
W0219 17:07:23.864000 1986836 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987619 closing signal SIGTERM
W0219 17:07:23.864000 1990262 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1990960 closing signal SIGTERM
W0219 17:07:23.864000 2033589 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2033748 closing signal SIGTERM
W0219 17:07:23.864000 1986959 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987093 closing signal SIGTERM
W0219 17:07:23.864000 1985442 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1986208 closing signal SIGTERM
W0219 17:07:23.864000 2110507 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2110636 closing signal SIGTERM
W0219 17:07:23.864000 1982123 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1982254 closing signal SIGTERM
W0219 17:07:23.864000 1987887 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1988021 closing signal SIGTERM
W0219 17:07:23.864000 1986836 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987620 closing signal SIGTERM
W0219 17:07:23.864000 1983838 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1984031 closing signal SIGTERM
W0219 17:07:23.865000 2110507 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2110637 closing signal SIGTERM
W0219 17:07:23.865000 1985034 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1985781 closing signal SIGTERM
W0219 17:07:23.865000 1986959 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987094 closing signal SIGTERM
W0219 17:07:23.862000 651329 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 651749 closing signal SIGTERM
W0219 17:07:23.864000 651329 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 651750 closing signal SIGTERM
W0219 17:07:23.865000 1986836 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987621 closing signal SIGTERM
W0219 17:07:23.865000 1988962 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1989696 closing signal SIGTERM
W0219 17:07:23.865000 1983947 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1984428 closing signal SIGTERM
W0219 17:07:23.865000 1985442 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1986209 closing signal SIGTERM
W0219 17:07:23.865000 1990262 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1990961 closing signal SIGTERM
W0219 17:07:23.865000 1983838 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1984032 closing signal SIGTERM
W0219 17:07:23.865000 1987887 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1988022 closing signal SIGTERM
W0219 17:07:23.865000 1985034 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1985782 closing signal SIGTERM
W0219 17:07:23.865000 2110507 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2110638 closing signal SIGTERM
W0219 17:07:23.865000 651329 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 651751 closing signal SIGTERM
W0219 17:07:23.865000 1986959 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987095 closing signal SIGTERM
W0219 17:07:23.865000 1986836 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987622 closing signal SIGTERM
W0219 17:07:23.866000 1983838 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1984033 closing signal SIGTERM
W0219 17:07:23.866000 1987087 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987851 closing signal SIGTERM
W0219 17:07:23.866000 1985442 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1986210 closing signal SIGTERM
W0219 17:07:23.865000 661040 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 661166 closing signal SIGTERM
W0219 17:07:23.865000 1990262 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1990962 closing signal SIGTERM
W0219 17:07:23.866000 1982123 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1982255 closing signal SIGTERM
W0219 17:07:23.866000 1988962 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1989697 closing signal SIGTERM
W0219 17:07:23.866000 1990262 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1990963 closing signal SIGTERM
W0219 17:07:23.866000 1983947 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1984429 closing signal SIGTERM
W0219 17:07:23.866000 2033589 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2033749 closing signal SIGTERM
W0219 17:07:23.866000 1986836 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987623 closing signal SIGTERM
W0219 17:07:23.866000 1987887 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1988023 closing signal SIGTERM
W0219 17:07:23.866000 1986959 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987096 closing signal SIGTERM
W0219 17:07:23.866000 1985034 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1985783 closing signal SIGTERM
W0219 17:07:23.866000 661040 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 661167 closing signal SIGTERM
W0219 17:07:23.866000 651329 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 651752 closing signal SIGTERM
W0219 17:07:23.866000 1982123 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1982256 closing signal SIGTERM
W0219 17:07:23.866000 2033589 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2033750 closing signal SIGTERM
W0219 17:07:23.866000 1983947 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1984430 closing signal SIGTERM
W0219 17:07:23.866000 1987887 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1988024 closing signal SIGTERM
W0219 17:07:23.866000 1983838 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1984034 closing signal SIGTERM
W0219 17:07:23.867000 1982123 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1982257 closing signal SIGTERM
W0219 17:07:23.867000 1983947 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1984431 closing signal SIGTERM
W0219 17:07:23.867000 2033589 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2033751 closing signal SIGTERM
W0219 17:07:23.867000 1987087 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987852 closing signal SIGTERM
W0219 17:07:23.867000 1987887 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1988025 closing signal SIGTERM
W0219 17:07:23.867000 1988962 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1989698 closing signal SIGTERM
W0219 17:07:23.867000 661040 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 661168 closing signal SIGTERM
W0219 17:07:23.867000 1985034 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1985784 closing signal SIGTERM
W0219 17:07:23.867000 1985442 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1986211 closing signal SIGTERM
W0219 17:07:23.867000 1990262 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1990964 closing signal SIGTERM
W0219 17:07:23.867000 1983838 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1984035 closing signal SIGTERM
W0219 17:07:23.867000 651329 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 651753 closing signal SIGTERM
W0219 17:07:23.867000 1985034 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1985785 closing signal SIGTERM
W0219 17:07:23.867000 1985442 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1986212 closing signal SIGTERM
W0219 17:07:23.867000 1987087 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987853 closing signal SIGTERM
W0219 17:07:23.867000 2110507 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2110639 closing signal SIGTERM
W0219 17:07:23.868000 661040 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 661169 closing signal SIGTERM
W0219 17:07:23.868000 651329 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 651754 closing signal SIGTERM
W0219 17:07:23.868000 1988962 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1989699 closing signal SIGTERM
W0219 17:07:23.868000 2110507 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2110640 closing signal SIGTERM
W0219 17:07:23.868000 661040 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 661170 closing signal SIGTERM
W0219 17:07:23.868000 1987087 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987854 closing signal SIGTERM
W0219 17:07:23.868000 651329 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 651755 closing signal SIGTERM
W0219 17:07:23.869000 1987087 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1987855 closing signal SIGTERM
W0219 17:07:23.854000 673195 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0219 17:07:23.870000 673195 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 673324 closing signal SIGTERM
W0219 17:07:23.872000 673195 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 673325 closing signal SIGTERM
W0219 17:07:23.872000 673195 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 673326 closing signal SIGTERM
W0219 17:07:23.874000 673195 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 673327 closing signal SIGTERM
W0219 17:07:23.875000 673195 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 673328 closing signal SIGTERM
W0219 17:07:23.877000 673195 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 673329 closing signal SIGTERM
W0219 17:07:23.877000 673195 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 673330 closing signal SIGTERM
W0219 17:07:23.878000 673195 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 673331 closing signal SIGTERM
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 855, in _invoke_run
    time.sleep(monitor_interval)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 855, in _invoke_run
    time.sleep(monitor_interval)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 661040 got signal: 15
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 855, in _invoke_run
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 2033589 got signal: 15
    time.sleep(monitor_interval)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 855, in _invoke_run
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    time.sleep(monitor_interval)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 651329 got signal: 15
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 673195 got signal: 15
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 855, in _invoke_run
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    time.sleep(monitor_interval)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
torch.distributed.elastic.multiprocessing.api.SignalException: Process 2110507 got signal: 15
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 855, in _invoke_run
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    time.sleep(monitor_interval)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 855, in _invoke_run
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 1986959 got signal: 15
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 855, in _invoke_run
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    time.sleep(monitor_interval)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    time.sleep(monitor_interval)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 1987087 got signal: 15
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 1986836 got signal: 15
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 855, in _invoke_run
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    time.sleep(monitor_interval)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 855, in _invoke_run
    time.sleep(monitor_interval)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 1983947 got signal: 15
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 1990262 got signal: 15
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 855, in _invoke_run
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    time.sleep(monitor_interval)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 1987887 got signal: 15
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 855, in _invoke_run
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    time.sleep(monitor_interval)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 855, in _invoke_run
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    time.sleep(monitor_interval)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 1988962 got signal: 15
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 1982123 got signal: 15
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 855, in _invoke_run
    time.sleep(monitor_interval)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 1985442 got signal: 15
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 855, in _invoke_run
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 855, in _invoke_run
    time.sleep(monitor_interval)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    time.sleep(monitor_interval)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 1983838 got signal: 15
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 1985034 got signal: 15