nielsr HF Staff commited on
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Add pipeline tag and library name, link to code

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This PR improves the model card by:
- adding a link to the Github repository
- adding a pipeline tag, ensuring it can be found at https://huggingface.co/models?pipeline_tag=image-text-to-text
- ensuring the model can be used using the appropriate auto classes of the Transformers library.

Files changed (1) hide show
  1. README.md +6 -3
README.md CHANGED
@@ -1,7 +1,9 @@
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  ---
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- license: mit
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  base_model:
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  - lmms-lab/llava-onevision-qwen2-7b-ov
 
 
 
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  ---
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  # llava-onevision-qwen2-7b-ov-unifiedreward-dpo
@@ -16,7 +18,7 @@ For further details, please refer to the following resources:
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  - πŸ€— Model Collections: https://huggingface.co/collections/CodeGoat24/unifiedreward-models-67c3008148c3a380d15ac63a
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  - πŸ€— Dataset Collections: https://huggingface.co/collections/CodeGoat24/unifiedreward-training-data-67c300d4fd5eff00fa7f1ede
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  - πŸ‘‹ Point of Contact: [Yibin Wang](https://codegoat24.github.io)
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-
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  ### Quick Start
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@@ -50,7 +52,8 @@ image_tensor = process_images([image], image_processor, model.config)
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  image_tensor = [_image.to(dtype=torch.float16, device=device) for _image in image_tensor]
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  conv_template = "qwen_1_5" # Make sure you use correct chat template for different models
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- question = DEFAULT_IMAGE_TOKEN + "\nWhat is shown in this image?"
 
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  conv = copy.deepcopy(conv_templates[conv_template])
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  conv.append_message(conv.roles[0], question)
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  conv.append_message(conv.roles[1], None)
 
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  ---
 
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  base_model:
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  - lmms-lab/llava-onevision-qwen2-7b-ov
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+ license: mit
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+ library_name: transformers
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+ pipeline_tag: image-text-to-text
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  ---
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  # llava-onevision-qwen2-7b-ov-unifiedreward-dpo
 
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  - πŸ€— Model Collections: https://huggingface.co/collections/CodeGoat24/unifiedreward-models-67c3008148c3a380d15ac63a
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  - πŸ€— Dataset Collections: https://huggingface.co/collections/CodeGoat24/unifiedreward-training-data-67c300d4fd5eff00fa7f1ede
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  - πŸ‘‹ Point of Contact: [Yibin Wang](https://codegoat24.github.io)
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+ - πŸ› οΈ Code: https://github.com/CodeGoat24/UnifiedReward
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  ### Quick Start
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  image_tensor = [_image.to(dtype=torch.float16, device=device) for _image in image_tensor]
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  conv_template = "qwen_1_5" # Make sure you use correct chat template for different models
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+ question = DEFAULT_IMAGE_TOKEN + "
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+ What is shown in this image?"
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  conv = copy.deepcopy(conv_templates[conv_template])
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  conv.append_message(conv.roles[0], question)
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  conv.append_message(conv.roles[1], None)