Create README.md

README.md

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+---
+tags:
+- vision-language model
+- llama
+- video understanding
+---
+
+
+# LLaMA-VID Model Card
+<a href='https://llama-vid.github.io/'><img src='https://img.shields.io/badge/Project-Page-Green'></a> 
+<a href='https://arxiv.org/abs/2311.17043'><img src='https://img.shields.io/badge/Paper-Arxiv-red'></a>
+
+## Model details
+LLaMA-VID empowers existing frameworks to support hour-long videos and pushes their upper limit with an extra context token.
+
+
+**Model type:**
+LLaMA-VID is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on GPT-generated multimodal instruction-following data.
+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.
+
+
+**Model date:**
+llama-vid-7b-full-224 was trained on 10/2023.
+
+## 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/dvlab-research/LLaMA-VID/issues
+
+## Intended use
+**Primary intended uses:**
+The primary use of LLaMA-VID is research on large multimodal models and chatbots.
+
+**Primary intended users:**
+The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.
+
+## Training data
+This model is trained based on LLaVA-1.5 dataset, including
+- 558K filtered image-text pairs from LAION/CC/SBU, captioned by BLIP.
+- 158K GPT-generated multimodal instruction-following data.
+- 450K academic-task-oriented VQA data mixture.
+- 40K ShareGPT data.