a43992899 commited on
Commit
7f9edce
β€’
1 Parent(s): 1ac66ba

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +2 -1
README.md CHANGED
@@ -16,8 +16,9 @@ Welcome to join us!
16
  Organization page: https://m-a-p.ai
17
 
18
  The development log of our Multimodal Art Projection (m-a-p) model family:
 
19
  - 23/01/2024: we release [**CMMMU**](https://huggingface.co/datasets/m-a-p/CMMMU) for better Chinese LMMs' Evaluation.
20
- - 13/01/2024: πŸ”₯ we release a series of **Music Pretrained Transformer (MuPT)** checkpoints, with [**size up to 1.3B and 8192 context length**](https://huggingface.co/m-a-p/MuPT_v0_8192_1.3B). Our models are **LLAMA2**-based, pre-trained on **world's largest 10B tokens symbolic music dataset** ([ABC notation format](https://en.wikipedia.org/wiki/ABC_notation)). We currently support Megatron-LM format and will release huggingface checkpoints soon.
21
  - 02/06/2023: officially release the [MERT pre-print paper](https://arxiv.org/abs/2306.00107) and training [codes](https://github.com/yizhilll/MERT).
22
  - 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.
23
  - 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)
 
16
  Organization page: https://m-a-p.ai
17
 
18
  The development log of our Multimodal Art Projection (m-a-p) model family:
19
+ - **πŸ”₯[2024-2-28]: The release of [ChatMusician](https://huggingface.co/collections/m-a-p/chatmusician-65de07b3b87b189c2a588329)'s demo, code, model, data, and benchmark. πŸ˜† **
20
  - 23/01/2024: we release [**CMMMU**](https://huggingface.co/datasets/m-a-p/CMMMU) for better Chinese LMMs' Evaluation.
21
+ - 13/01/2024: we release a series of **Music Pretrained Transformer (MuPT)** checkpoints, with [**size up to 1.3B and 8192 context length**](https://huggingface.co/m-a-p/MuPT_v0_8192_1.3B). Our models are **LLAMA2**-based, pre-trained on **world's largest 10B tokens symbolic music dataset** ([ABC notation format](https://en.wikipedia.org/wiki/ABC_notation)). We currently support Megatron-LM format and will release huggingface checkpoints soon.
22
  - 02/06/2023: officially release the [MERT pre-print paper](https://arxiv.org/abs/2306.00107) and training [codes](https://github.com/yizhilll/MERT).
23
  - 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.
24
  - 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)