audiocraft 1.3.0

The Audiocraft library is a powerful tool for audio processing and generation using deep learning. Developed by Facebook Research, it includes the Encodec audio compressor tokenizer and MusicGen, a language model for music generation that can be controlled with text and melody. This makes it a valuable resource for developers and researchers interested in music generation and audio processing. The library is built on PyTorch and requires a GPU for operation.

Stars: 20747, Watchers: 20747, Forks: 2113, Open Issues: 300

The facebookresearch/audiocraft repo was created 1 years ago and the last code push was 2 months ago.
The project is extremely popular with a mindblowing 20747 github stars!

How to Install audiocraft

You can install audiocraft using pip

pip install audiocraft

or add it to a project with poetry

poetry add audiocraft

Package Details

Author

FAIR Speech & Audio

License

MIT License

Homepage

https://github.com/facebookresearch/audiocraft

PyPi:

https://pypi.org/project/audiocraft/

GitHub Repo:

https://github.com/facebookresearch/audiocraft

Classifiers

• Multimedia/Sound/Audio
• Scientific/Engineering/Artificial Intelligence

Related Packages

Errors

A list of common audiocraft errors.

Code Examples

Here are some audiocraft code examples and snippets.

GitHub Issues

The audiocraft package has 300 open issues on GitHub

• Audio Embeddings
• Can't find Seed?
• FFMPEG not found?
• Version conflicts with hydra-core
• –listen - how to make it work?
• Is it possible to use multiple GPU for single generate?
• Release Date of Traning Code
• Can anyone explain how the top_p and top_k parameter affects the output of the model?
• Update Readme: Add links to Replicate deployment of MusicGen
• how to train and how much data to invest so that there is no noise?
• Non-Usable download from Gradio?
• Any chance for adjust the sample and bit rate of WAVs up?
• help by install
• How to download file using api
• HuggingFace

See more issues on GitHub