audiocraft
facebookresearch/audiocraft · Jupyter Notebook · MIT
MusicGen and companion models for text-to-music
この解説はまだ日本語がありません。英語の原文を表示しています。
AudioCraft is Meta’s research toolkit behind MusicGen. It is still one of the easiest ways to try controllable text-to-music locally with solid docs.
スコア
導入の要点
pip install -U audiocraft 深読み
AudioCraft is Meta's codebase for neural audio generation: it hosts the family of models that defined the text-to-audio wave — MusicGen for text-to-music, AudioGen for text-to-sound, EnCodec for high-fidelity neural compression, and Multi Band Diffusion as an EnCodec-compatible decoder.
Each model is documented in its own guide with training and inference code, which is what made AudioCraft the reference implementation a generation of audio projects forked from.
It is a research codebase: expect to configure checkpoints and environments yourself, and to read the per-model docs before running anything serious.