metadata
license: mit
pipeline_tag: other
tags:
- music
- SSL
- pytorch
Frequency-Aware Self-Supervised Music Representation Learning
This is the official Hugging Face model repository for the paper "Frequency-Aware Self-Supervised Music Representation Learning".
- Project Page: https://www.yichenggu.com/PupuM2D/
- GitHub Repository: https://github.com/sizigi/PupuM2D/
Model Checkpoints
This repository contains the following checkpoints:
| Model Name | Directory | Description |
|---|---|---|
| PupuM2D-Tiny | ./PupuM2DV2_25Hz_tiny/* |
5M parameter tiny version of PupuM2D. |
| PupuM2D-Small | ./PupuM2DV2_25Hz_small/* |
22M parameter small version of PupuM2D. |
| PupuM2D-Base | ./PupuM2DV2_25Hz_base/* |
86M parameter base version of PupuM2D. |
| PupuM2D-Large | ./PupuM2DV2_25Hz_large/* |
307M parameter large version of PupuM2D. |
| PupuM2D-Huge | ./PupuM2DV2_25Hz_huge/* |
632M parameter huge version of PupuM2D. |
| PupuM2D-giant | ./PupuM2DV2_25Hz_giant/* |
1.1B parameter giant version of PupuM2D. |
How to use
You need to put the pretrained models in:
PupuM2D/experiments
of our official repository.
Citation
@article{PupuM2D,
title = {Frequency-Aware Self-Supervised Music Representation Learning},
author = {Yicheng Gu and Junan Zhang and Jerry Li and Zhizheng Wu and Lauri Juvela},
year = {2026},
journal = {arXiv:2606.25713},
}