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---
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license: apache-2.0
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inference: false
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---
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<br>
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<br>
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# Matryoshka Multimodal Models (M3) Model Card
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## Model details
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**Model type:**
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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.
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M3s is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on visual conversation data.
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It is an auto-regressive language model, based on the transformer architecture.
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**Model date:**
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llava-next-vicuna-7b-m3 was trained in May 2024. [Paper](https://arxiv.org/abs/2405.17430)
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**Paper or resources for more information:**
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https://matryoshka-mm.github.io/
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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/mu-cai/matryoshka-mm/issues
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## Intended use
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**Primary intended uses:**
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The primary use of M3 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 dataset
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- 558K filtered image-text pairs from LAION/CC/SBU, captioned by BLIP.
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- 665K image level instruction data from LLaVA-1.5.
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## Evaluation dataset
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Matryoshka Multimodal Models (M3) achieves strong performance even using 1 or 9 visual tokens per image.
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