---
library_name: diffusers
tags:
- music
---

# Official Hugging Face Diffusers Implementation of QA-MDT 
**QAMDT: Quality-Aware Diffusion for Text-to-Music 🎶**

QADMT brings a new approach to text-to-music generation by using quality-aware training to tackle issues like low-fidelity audio and weak labeling in datasets. 

With a masked diffusion transformer (MDT), QADMT delivers SOTA results on MusicCaps and Song-Describer, enhancing both quality and musicality. 

Here’s the revised version with "et al.":

It follows from [this paper](https://arxiv.org/pdf/2405.15863) by the University of Science and Technology of China, authored by [@changli](https://github.com/ivcylc) *et al.*.
## Usage:

```bash
!git lfs install
!git clone https://huggingface.co/jadechoghari/openmusic
```

Manually change the folder name from `openmusic` to `qa_mdt`

```bash
pip install -r qa_mdt/requirements.txt
pip install xformers==0.0.26.post1
pip install torchlibrosa==0.0.9 librosa==0.9.2
pip install -q pytorch_lightning==2.1.3 torchlibrosa==0.0.9 librosa==0.9.2 ftfy==6.1.1 braceexpand
pip install torch==2.3.0+cu121 torchvision==0.18.0+cu121 torchaudio==2.3.0 --index-url https://download.pytorch.org/whl/cu121
```

```python
from qa_mdt.pipeline import MOSDiffusionPipeline

pipe = MOSDiffusionPipeline()
pipe("A modern synthesizer creating futuristic soundscapes.")
```

# Enjoy the music!! 🎶