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README.md

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+# Matryoshka Multimodal Models (M3) Model Card
+
+## Model details
+
+**Model type:**
+Matryoshka Multimodal Models (M3) allow using to explicitly control visual granularities (the number of visual toknes per sample) at time time. Also, the model itself serves as a metric for image/dataset complexity. 
+M3s is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on visual conversation data.
+It is an auto-regressive language model, based on the transformer architecture.
+
+**Model date:**
+llava-next-vicuna-7b-m3 was trained in May 2024. [Paper](https://arxiv.org/abs/2405.17430)
+
+**Paper or resources for more information:**
+https://matryoshka-mm.github.io/
+
+## 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/mu-cai/matryoshka-mm/issues
+
+## Intended use
+**Primary intended uses:**
+The primary use of M3 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 dataset
+- 558K filtered image-text pairs from LAION/CC/SBU, captioned by BLIP.
+- 665K image level instruction data from LLaVA-1.5.
+
+## Evaluation dataset
+Matryoshka Multimodal Models (M3) achieves strong performance even using 1 or 9 visual tokens per image.
+