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---

license: apache-2.0
inference: false
---



<br>
<br>

# 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.