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MusicMamba

This is the official implementation of MusicMamba.

Checkout our demo and paper : Demo | arXiv

Environment

  • Clone this Repo

    git clone https://github.com/Wietc/MusicMamba.git
    
  • using python version 3.11.5

  • using pytorch version 2.2.1

  • install python dependencies

    pip install -r requirements.txt

  • Mamba needs to be downloaded separately

    pip install mamba_ssm

  • install checkpoints from Huggingface

To train the model with GPU

We currently do not offer fine-tuning functionality.

To generate music

python generate.py

Details of the files in this repo

`
β”œβ”€β”€ data                    Stores train, test and val data.
β”‚   └── FolkDB              
β”‚       β”œβ”€β”€ train
β”‚       β”œβ”€β”€ test
β”‚       └── val
β”œβ”€β”€ dataset.py              Progress datasets.
β”œβ”€β”€ generate.py             For generating music. (Detailed usage are written in the file)
β”œβ”€β”€ model.py                The MusicMamba Architecture.
β”œβ”€β”€ midi_tokenize           Remi-M tokenize.
β”œβ”€β”€ utilities               Tools for generating music.
β”‚   β”œβ”€β”€ argument_funcs.py   Some arguments for generating.
β”‚   β”œβ”€β”€ constants.py        
β”‚   └── device.py           
└── README.md              Readme

Citation

If you find this work helpful and use our code in your research, please kindly cite our paper:

@article{MusicMamba,
title={MusicMamba: A Dual-Feature Modeling Approach for Generating Chinese Traditional Music with Modal Precision},
author={Jiatao Chen and Xing Tang and Tianming Xie and Jing Wang and Wenjing Dong and Bing Shi}, year={2024},
eprint={2409.02421},
archivePrefix={arXiv},
}
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