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README.md

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+inference: false
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+<br>
+
+# LLaVA-Next-Video Model Card
+
+## Model details
+
+**Model type:**
+<br>
+LLaVA-Next-Video is an open-source chatbot trained by fine-tuning LLM on multimodal instruction-following data.
+<br>
+ Base LLM: lmsys/vicuna-7b-v1.5
+
+**Model date:**
+<br>
+LLaVA-Next-Video-7B-DPO was trained in April 2024.
+
+**Paper or resources for more information:**
+<br>
+https://github.com/LLaVA-VL/LLaVA-NeXT
+
+## License
+Llama 2 is licensed under the LLAMA 2 Community License, 
+Copyright (c) Meta Platforms, Inc. All Rights Reserved.
+
+## Where to send questions or comments about the model
+https://github.com/LLaVA-VL/LLaVA-NeXT/issues
+
+## Intended use
+**Primary intended uses:**
+<br>
+The primary use of LLaVA is research on large multimodal models and chatbots.
+
+**Primary intended users:**
+<br>
+The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.
+
+## Training dataset
+
+### Image
+- 558K filtered image-text pairs from LAION/CC/SBU, captioned by BLIP.
+- 158K GPT-generated multimodal instruction-following data.
+- 500K academic-task-oriented VQA data mixture.
+- 50K GPT-4V data mixture.
+- 40K ShareGPT data.
+### Video
+- 100K VideoChatGPT-Instruct.
+- 17k video preference data: https://huggingface.co/datasets/ShareGPTVideo/train_video_and_instruction
+
+## Evaluation dataset
+A collection of 4 benchmarks, including 3 academic VQA benchmarks and 1 captioning benchmark.