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@@ -29,16 +29,22 @@ Play with the model on the [LLaVA OneVision Chat](https://llava-onevision.lmms-l
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  ## Model Summary
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- The LLaVA-OneVision models are 0.5/7/72B parameter models trained on [LLaVA-OneVision](https://huggingface.co/datasets/lmms-lab/LLaVA-OneVision-Data), based on Qwen2 language model with a context window of 32K tokens.
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- The model with `-chat` postfix denotes the model with iterative DPO training with human preference and suitable for chat usage. Our research shows we can improve the model's chat ability meanwhile maintain other instruction-following abilities through our iterative DPO training recipe.
 
 
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  - **Repository:** [LLaVA-VL/LLaVA-NeXT](https://github.com/LLaVA-VL/LLaVA-NeXT?tab=readme-ov-file)
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  - **Project Website:** [llava-onevision.lmms-lab.com](llava-onevision.lmms-lab.com)
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  - **Paper:** [LLaVA-OneVision](arxiv.org/abs/2408.03326)
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- - **Point of Contact:** [Bo Li](mailto:drluodian@gmail.com)
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  - **Languages:** English, Chinese
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  ## Use
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  ### Intended use
 
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  ## Model Summary
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+ `llava-onevision-72b-ov-chat` is our latest model specifically designed for chat scenarios. It is built upon `llava-onevision-72b-ov` and has undergone iterative DPO training with human preference, making it well-suited for chat applications.
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+ Research by [Tianyi Xiong](https://tyxiong23.github.io/) indicates that our iterative DPO training method enhances the model's chat capabilities while preserving its instruction-following abilities.
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+ For further details, please refer to our upcoming blog or paper.
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  - **Repository:** [LLaVA-VL/LLaVA-NeXT](https://github.com/LLaVA-VL/LLaVA-NeXT?tab=readme-ov-file)
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  - **Project Website:** [llava-onevision.lmms-lab.com](llava-onevision.lmms-lab.com)
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  - **Paper:** [LLaVA-OneVision](arxiv.org/abs/2408.03326)
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+ - **Point of Contact:** [Tianyi Xiong](https://tyxiong23.github.io/), [Bo Li](mailto:drluodian@gmail.com)
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  - **Languages:** English, Chinese
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+ ## Benchmark Performance
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+ To be released
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  ## Use
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  ### Intended use