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

  https://huggingface.co/moersxm12138/MusicMamba

To train the model with GPU

We currently do not offer fine-tuning functionality.

To generate music

python generate.py

• The specification of the model path, data path, and other generated parameters are in the utilities/argument_funcs.py file.

Details of the files in this repo

`
├── data                    Stores train, test and val data.
│   └── FolkDB              
│       ├── train
│       ├── test
│       └── val
├── dataset.py              Progress datasets.
├── generate.py             For generating music. (Detailed usage are written in the file)
├── model.py                The MusicMamba Architecture.
├── midi_tokenize           Remi-M tokenize.
├── utilities               Tools for generating music.
│   ├── argument_funcs.py   Some arguments for generating.
│   ├── constants.py        
│   └── 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},
}