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Update pipeline_tag and add library_name for R-4B (#1)

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- Update pipeline_tag and add library_name for R-4B (276aae44fc63abc67d362c52d18c2d9be67a3dbc)


Co-authored-by: Niels Rogge <[email protected]>

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  1. README.md +7 -5
README.md CHANGED
@@ -1,11 +1,13 @@
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  ---
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- license: apache-2.0
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- language:
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- - en
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  base_model:
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  - Qwen/Qwen3-4B
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- pipeline_tag: visual-question-answering
 
 
 
 
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  ---
 
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  # R-4B: Incentivizing General-Purpose Auto-Thinking Capability in MLLMs via Bi-Mode Annealing and Reinforce Learning
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  [[πŸ“š Arxiv Paper](https://arxiv.org/pdf/2508.21113)] [[πŸ€— Hugging Face](https://huggingface.co/YannQi/R-4B)] [[πŸ€–οΈ ModelScope](https://huggingface.co/YannQi/R-4B)] [[πŸ’» Code](https://github.com/yannqi/R-4B)]
@@ -225,4 +227,4 @@ print("Chat response:", chat_response)
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  ## Acknowledgements
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- R-4B is developed based on the codebases of the following projects: [LLaVA-Next](https://github.com/LLaVA-VL/LLaVA-NeXT), [SigLIP2](https://huggingface.co/google/siglip2-so400m-patch14-384), [Qwen3](https://github.com/QwenLM/Qwen3), [Qwen2.5-VL](https://github.com/QwenLM/Qwen2.5-VL), [VLMEvalKit](https://github.com/open-compass/VLMEvalKit). We sincerely thank these projects for their outstanding work.
 
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  ---
 
 
 
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  base_model:
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  - Qwen/Qwen3-4B
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+ language:
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+ - en
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+ license: apache-2.0
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+ pipeline_tag: image-text-to-text
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+ library_name: transformers
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  ---
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+
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  # R-4B: Incentivizing General-Purpose Auto-Thinking Capability in MLLMs via Bi-Mode Annealing and Reinforce Learning
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  [[πŸ“š Arxiv Paper](https://arxiv.org/pdf/2508.21113)] [[πŸ€— Hugging Face](https://huggingface.co/YannQi/R-4B)] [[πŸ€–οΈ ModelScope](https://huggingface.co/YannQi/R-4B)] [[πŸ’» Code](https://github.com/yannqi/R-4B)]
 
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  ## Acknowledgements
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+ R-4B is developed based on the codebases of the following projects: [LLaVA-Next](https://github.com/LLaVA-VL/LLaVA-NeXT), [SigLIP2](https://huggingface.co/google/siglip2-so400m-patch14-384), [Qwen3](https://github.com/QwenLM/Qwen3), [Qwen2.5-VL](https://github.com/QwenLM/Qwen2.5-VL), [VLMEvalKit](https://github.com/open-compass/VLMEvalKit). We sincerely thank these projects for their outstanding work.