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Stable diffusion for real-time music generation
| Date | Stars |
|---|---|
| 2026-07-24 | 3900 |
| 2026-07-25 | 3900 |
| 2026-07-28 | 3900 |
| 2026-07-30 | 3900 |
| 2026-07-31 | 3900 |
| 2026-08-06 | 3900 |
Today
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0.0
growth rate 0.00%/day
# :guitar: Riffusion (hobby)
:no_entry: This project is no longer actively maintained.
<a href="https://github.com/riffusion/riffusion/actions/workflows/ci.yml?query=branch%3Amain"><img alt="CI status" src="https://github.com/riffusion/riffusion/actions/workflows/ci.yml/badge.svg" /></a>
<img alt="Python 3.9 | 3.10" src="https://img.shields.io/badge/Python-3.9%20%7C%203.10-blue" />
<a href="https://github.com/riffusion/riffusion/tree/main/LICENSE"><img alt="MIT License" src="https://img.shields.io/badge/License-MIT-yellowgreen" /></a>
Riffusion is a library for real-time music and audio generation with stable diffusion.
Read about it at https://www.riffusion.com/about and try it at https://www.riffusion.com/.
This is the core repository for riffusion image and audio processing code.
* Diffusion pipeline that performs prompt interpolation combined with image conditioning
* Conversions between spectrogram images and audio clips
* Command-line interface for common tasks
* Interactive app using streamlit
* Flask server to provide model inference via API
* Various third party integrations
Related repositories:
* Web app: https://github.com/riffusion/riffusion-app
* Model checkpoint: https://huggingface.co/riffusion/riffusion-model-v1
## Citation
If you build on this work, please cite it as follows:
```
@article{Forsgren_Martiros_2022,
author = {Forsgren, Seth* and Martiros, Hayk*},
title = {{Riffusion - Stable diffusion for real-time music generation}},
url = {https://riffusion.com/about},
year = {2022}
}
```
## Install
Tested in CI with Python 3.9 and 3.10.
It's highly recommended to set up a virtual Python environment with `conda` or `virtualenv`:
```
conda create --name riffusion python=3.9
conda activate riffusion
```
Install Python dependencies:
```
python -m pip install -r requirements.txt
```
In order to use audio formats other than WAV, [ffmpeg](https://ffmpeg.org/download.html) is required.
```
sudo apt-get install ffmpeg # linux
brew install ffmpeg # mac
conda install -c conda-forge ffmpeg # conda
```
If torchaudio has no backend, you may need to install `libsndfile`. See [this issue](https://github.com/riffusion/riffusion/issues/12).
If you have an issue, try upgrading [diffusers](https://github.com/huggingface/diffusers). Tested with 0.9 - 0.11.
Guides:
* [Simple Install Guide for Windows](https://www.reddit.com/r/riffusion/comments/zrubc9/installation_guide_for_riffusion_app_inference/)
## Backends
### CPU
`cpu` is supported but is quite slow.
### CUDA
`cuda` is the recommended and most performant backend.
To use with CUDA, make sure you have torch and torchaudio installed with CUDA support. See the
[install guide](https://pytorch.org/get-started/locally/) or
[stable wheels](https://download.pytorch.org/whl/torch_stable.html).
To generate audio in real-time, you need a GPU that can run stable diffusion with approximately 50
steps in under five seconds, such as a 3090 or A10G.
Test availability with:
```python3
import torch
torch.cuda.is_available()
```
### MPS
The `mps` backend on Apple Silicon is supported for inference but some operations fall back to CPU,
particularly for audio processing. You may need to set
`PYTORCH_ENABLE_MPS_FALLBACK=1`.
In addition, this backend is not deterministic.
Test availability with:
```python3
import torch
torch.backends.mps.is_available()
```
## Command-line interface
Riffusion comes with a command line interface for performing common tasks.
See available commands:
```
python -m riffusion.cli -h
```
Get help for a specific command:
```
python -m riffusion.cli image-to-audio -h
```
Execute:
```
python -m riffusion.cli image-to-audio --image spectrogram_image.png --audio clip.wav
```
## Riffusion Playground
Riffusion contains a [streamlit](https://streamlit.io/) app for interactive use and exploration.
Run with:
```
python -m riffusion.streamlit.playground
```
And access at http://127.0.0.1:8501/
<img alt="RiExcerpt of 6,336 characters
Read on GitHub
Hayk Martiros · Skydio · United States
114
Seth Forsgren · United States
9
3
2
1
ilayluz
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:b253d7602e6cf62a, topic:stable-diffusion, desc:stable diffusion, readme:stable diffusion