https://github.com/steve-mackinnon/stable-audio-open-modal
Python scripts for running stable audio open inference locally and on Modal
https://github.com/steve-mackinnon/stable-audio-open-modal
audio modal music-production python stable-audio stable-diffusion
Last synced: 6 months ago
JSON representation
Python scripts for running stable audio open inference locally and on Modal
- Host: GitHub
- URL: https://github.com/steve-mackinnon/stable-audio-open-modal
- Owner: steve-mackinnon
- Created: 2024-11-18T15:04:53.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2025-01-06T11:54:33.000Z (9 months ago)
- Last Synced: 2025-04-12T14:24:03.571Z (6 months ago)
- Topics: audio, modal, music-production, python, stable-audio, stable-diffusion
- Language: Python
- Homepage:
- Size: 13.7 KB
- Stars: 4
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Stable Audio Open Modal
This repo includes python code for running inference with the [Stable Audio Open 1.0](https://huggingface.co/stabilityai/stable-audio-open-1.0) model. This can be run locally or hosted on [Modal](https://modal.com).
`generate_audio_sample.py` tweaks the provided prompt to attempt to generate a oneshot sample like a drum hit. It then applies some post processing to the model output to trim extra hits and fade out the audio smoothly.
## Hugging Face setup
In order to access the Stable Audio Open model, you'll need to:
1. Create a [Hugging Face account](https://huggingface.co/)
2. Navigate to the [Stable Audio Open 1.0](https://huggingface.co/stabilityai/stable-audio-open-1.0) model page and opt-in to gain access to the model
3. Create a [Hugging Face access token](https://huggingface.co/settings/tokens/new?tokenType=read) with read access
4. Copy the token and add it to your local env using the name HF_TOKEN:
For zsh, add this to your `~/.zshrc`:
```bash
export HF_TOKEN=myhftoken
```
For fish, add this to your fish config (e.g. `~/.config/fish/config.fish`):
```bash
set -Ux HF_TOKEN myhftoken
```
## Local environment setup
1. Install miniconda: https://docs.conda.io/en/latest/miniconda.html
2. Setup the conda environment
```bash
conda env create -f environment.yml
```
3. Activate it
```bash
conda activate stable-audio-open-modal
```
## Running locally
To run inference locally, you can run `generate_audio.py` after activating the conda environment.
For example:
```bash
python generate_audio.py --prompt "Massive metalic techno kick drum"
```
This will generate a file called `output_0.wav` in the current directory.
To see a list of available arguments to customize inference, run:
```bash
python generate_audio.py -h"
```
## Running on Modal
To deploy the app to run inference on [Modal](https://modal.com), you'll need to:
1. Create a Modal account
2. Create a Hugging Face account and API token.
3. Sign the agreement to use the [Stable Audio Open 1.0](https://huggingface.co/stabilityai/stable-audio-open-1.0) model.
4. Setup secrets for the Modal app with the following environment variables:
- `HF_TOKEN`: Your Hugging Face API token
- `AUTH_TOKEN`: A Bearer auth token you create to authenticate requests to the Modal app
5. Deploy the app with the following command:
```bash
modal deploy src/api.py
```
Note, you can test the endpoint prior to deploying with the following command:
```bash
modal serve src/api.py
```
And hit the endpoint with a POST request locally. This assumes you have set the `AUTH_TOKEN` environment variable.
```bash
curl -X POST https://your-modal-endpoint.modal.run \
-H "Authorization: Bearer "$AUTH_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"prompt": "Dub techno snare"
}' --output "modal-out.wav"
```