---
license: apache-2.0
tags:
- code
- music
---
# From Generality to Mastery: Composer-Style Conditioned Music Generation
Trained model weights and training datasets for the paper:
  * Mingyang Yao and Ke Chen
    "[From Generality to Mastery: Composer-Style Symbolic Music Generation via Large-Scale Pre-training](https://arxiv.org/abs/2506.17497)."  
    _Conference of AI Music Creativity (AIMC)_, 2025

**Note:** Please find project details and usage at our [Github repo](https://github.com/AndyWeasley2004/Generality-to-Mastery)

## Model Architecture
### "Generality" Stage
The model learns **general** music patterns and knowledge from diverse genres of music
  - Model backbone: 12-layer Transformer with relative positional encoding
  - Num trainable params: 39.6M

### "Mastery" Stage
The model adapts its knowledge to specific composers' characteristics
  - Model backbone: 12-layer Transformer with relative positional encoding plus adapter modules inserted after every two transformer layers
  - Num trainable params: 46M

## Citation
If you find this project useful, please cite our paper:
```
@inproceedings{generalitymastery2025,
  author = {Mingyang Yao and Ke Chen},
  title = {From Generality to Mastery: Composer-Style Symbolic Music Generation via Large-Scale Pre-training},
  booktitle={Proceedings of the AI Music Creativity, {AIMC}},
  year = {2025}
}
```