--- license: apache-2.0 inference: false ---

# 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.