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--- |
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inference: false |
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license: apache-2.0 |
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--- |
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<br> |
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<br> |
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# LLaVA-Hound Model Card |
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## Model details |
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**Model type:** |
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LLaVA-Hound is an open-source video large multimodal model, fine-tuned from video instruction following data based on large language model. |
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This model is the **pre-trained** ckpt on **image and video caption** data. |
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Base LLM: [lmsys/vicuna-7b-v1.5](https://huggingface.co/lmsys/vicuna-7b-v1.5) |
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**Model date:** |
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Trained on March 15, 2024. |
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**Paper or resources for more information:** |
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https://github.com/RifleZhang/LLaVA-Hound-DPO |
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## License |
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[lmsys/vicuna-7b-v1.5](https://huggingface.co/lmsys/vicuna-7b-v1.5) license. |
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**Where to send questions or comments about the model:** |
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https://github.com/RifleZhang/LLaVA-Hound-DPO/issues |
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## Intended use |
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**Primary intended uses:** |
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Video detailed captioning |
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**Primary intended users:** |
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Researchers in artificial intelligence, large multimodal model, etc. |
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## Training dataset |
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ShareGPTVideo dataset. |
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## Evaluation |
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Follow https://github.com/RifleZhang/LLaVA-Hound-DPO/blob/main/README.md |
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## Paper |
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https://huggingface.co/papers/2404.01258 |
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citation |
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``` |
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@article{zhang2024direct, |
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title={Direct Preference Optimization of Video Large Multimodal Models from Language Model Reward}, |
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author={Zhang, Ruohong and Gui, Liangke and Sun, Zhiqing and Feng, Yihao and Xu, Keyang and Zhang, Yuanhan and Fu, Di and Li, Chunyuan and Hauptmann, Alexander and Bisk, Yonatan and others}, |
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journal={arXiv preprint arXiv:2404.01258}, |
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year={2024} |
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} |
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``` |
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