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- A Large Multimodal Reasoning Model.
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  ```
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  from transformers import Qwen2_5_VLForConditionalGeneration, AutoTokenizer, AutoProcessor
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  from qwen_vl_utils import process_vision_info
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  generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
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  )
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  print(output_text)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
 
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+ # A Large Multimodal Reasoning Model.
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+ ## Usage
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  ```
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  from transformers import Qwen2_5_VLForConditionalGeneration, AutoTokenizer, AutoProcessor
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  from qwen_vl_utils import process_vision_info
 
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  generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
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  )
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  print(output_text)
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+ ```
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+
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+ ## Citations
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+ ```
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+ @misc {di_zhang_2025,
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+ author = { {Di Zhang} },
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+ title = { Qwen2.5-VL-7B-R1-Distillation (Revision 6cc3c46) },
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+ year = 2025,
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+ url = { https://huggingface.co/di-zhang-fdu/Qwen2.5-VL-7B-R1-Distillation },
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+ doi = { 10.57967/hf/4710 },
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+ publisher = { Hugging Face }
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+ }
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+
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+ @article{zhang2024critic,
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+ title={Critic-V: VLM Critics Help Catch VLM Errors in Multimodal Reasoning},
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+ author={Zhang, Di and Lei, Jingdi and Li, Junxian and Wang, Xunzhi and Liu, Yujie and Yang, Zonglin and Li, Jiatong and Wang, Weida and Yang, Suorong and Wu, Jianbo and others},
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+ journal={arXiv preprint arXiv:2411.18203},
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+ year={2024}
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+ }
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  ```