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README.md

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+---
+library_name: transformers.js
+base_model:
+- date3k2/vit-real-fake-classification-v4
+---
+
+# vit-real-fake-classification-v4 (ONNX)
+
+This is an ONNX version of [date3k2/vit-real-fake-classification-v4](https://huggingface.co/date3k2/vit-real-fake-classification-v4). It was automatically converted and uploaded using [this space](https://huggingface.co/spaces/onnx-community/convert-to-onnx).

config.json

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+{
+  "_attn_implementation_autoset": true,
+  "_name_or_path": "date3k2/vit-real-fake-classification-v4",
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "Fake",
+    "1": "Real"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Fake": "0",
+    "Real": "1"
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "vit",
+  "num_attention_heads": 12,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "patch_size": 16,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.49.0"
+}

onnx/model.onnx

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+size 343401688

onnx/model_bnb4.onnx

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onnx/model_fp16.onnx

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onnx/model_int8.onnx

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+size 87333629

onnx/model_q4.onnx

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onnx/model_q4f16.onnx

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onnx/model_quantized.onnx

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onnx/model_uint8.onnx

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preprocessor_config.json

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+{
+  "do_convert_rgb": null,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "ViTFeatureExtractor",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

quantize_config.json

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+{
+    "modes": [
+        "fp16",
+        "q8",
+        "int8",
+        "uint8",
+        "q4",
+        "q4f16",
+        "bnb4"
+    ],
+    "per_channel": true,
+    "reduce_range": true,
+    "block_size": null,
+    "is_symmetric": true,
+    "accuracy_level": null,
+    "quant_type": 1,
+    "op_block_list": null
+}