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@@ -16,7 +16,7 @@ Welcome to join us!
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  Organization page: https://m-a-p.ai
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  The development log of our Multimodal Art Projection (m-a-p) model family:
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- - **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˜†**
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  - 23/01/2024: we release [**CMMMU**](https://huggingface.co/datasets/m-a-p/CMMMU) for better Chinese LMMs' Evaluation.
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  - 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.
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  - 02/06/2023: officially release the [MERT pre-print paper](https://arxiv.org/abs/2306.00107) and training [codes](https://github.com/yizhilll/MERT).
 
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  Organization page: https://m-a-p.ai
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  The development log of our Multimodal Art Projection (m-a-p) model family:
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+ - 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˜†
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  - 23/01/2024: we release [**CMMMU**](https://huggingface.co/datasets/m-a-p/CMMMU) for better Chinese LMMs' Evaluation.
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  - 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.
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  - 02/06/2023: officially release the [MERT pre-print paper](https://arxiv.org/abs/2306.00107) and training [codes](https://github.com/yizhilll/MERT).