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---
title: README
emoji: 👀
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colorTo: yellow
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---
Multimodal Art Projection (M-A-P) is an opensource research community.
The coummnity members are working on Artificial Intelligence-Generated Content (AIGC) topics, including text, audio, and vision modalities.
We do large language/music models (LLMs/LMMs) training, data collection, and development of fun applications.
Welcome to join us!
Organization page: https://m-a-p.ai
The development log of our Multimodal Art Projection (m-a-p) model family:
- 13/01/2024: We release a series of Music Pretrained Transformer (MuPT), [size up to 1.3B with 8192 context length](https://huggingface.co/m-a-p/MuPT_v0_8192_1.3B). Our LLaMA2-based models are pre-trained on world's largest symbolic music dataset with 10B tokens (ABC notation format). We currently support Megatron-LM format and will release huggingface checkpoints soon.
- 02/06/2023: officially release the [MERT pre-print paper](https://arxiv.org/abs/2306.00107) and training [codes](https://github.com/yizhilll/MERT).
- 17/03/2023: we release two advanced music understanding models, [MERT-v1-95M](https://huggingface.co/m-a-p/MERT-v1-95M) and [MERT-v1-330M](https://huggingface.co/m-a-p/MERT-v1-330M) , trained with new paradigm and dataset. They outperform the previous models and can better generalize to more tasks.
- 14/03/2023: we retrained the MERT-v0 model with open-source-only music dataset [MERT-v0-public](https://huggingface.co/m-a-p/MERT-v0-public)
- 29/12/2022: a music understanding model [MERT-v0](https://huggingface.co/m-a-p/MERT-v0) trained with **MLM** paradigm, which performs better at downstream tasks.
- 29/10/2022: a pre-trained MIR model [music2vec](https://huggingface.co/m-a-p/music2vec-v1) trained with **BYOL** paradigm. |