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README.md
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---
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tags:
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- vision-language model
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- llama
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- video understanding
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---
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# LLaMA-VID Model Card
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<a href='https://llama-vid.github.io/'><img src='https://img.shields.io/badge/Project-Page-Green'></a>
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<a href='https://arxiv.org/abs/2311.17043'><img src='https://img.shields.io/badge/Paper-Arxiv-red'></a>
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## Model details
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LLaMA-VID empowers existing frameworks to support hour-long videos and pushes their upper limit with an extra context token.
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**Model type:**
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LLaMA-VID is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on GPT-generated multimodal instruction-following data.
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LLaMA-VID empowers existing frameworks to support hour-long videos and pushes their upper limit with an extra context token. We build this repo based on LLaVA.
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**Model date:**
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llama-vid-7b-pretrain-224-video-fps-1 was trained on 11/2023.
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## License
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Llama 2 is licensed under the LLAMA 2 Community License,
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Copyright (c) Meta Platforms, Inc. All Rights Reserved.
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**Where to send questions or comments about the model:**
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https://github.com/dvlab-research/LLaMA-VID/issues
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## Intended use
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**Primary intended uses:**
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The primary use of LLaMA-VID is research on large multimodal models and chatbots.
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**Primary intended users:**
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The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.
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## Training data
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This model is trained based on image data from LLaVA-1.5 dataset, and video data from WebVid, including
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- 558K filtered image-text pairs from LAION/CC/SBU, captioned by BLIP.
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- 232K video-caption pairs sampled from the WebVid 2.5M dataset.
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