Musique IA
moises-light
A resource-efficient music source separation model in PyTorch.
★ 36 étoilesMIT
Voir le guide →moseca est un projet de musique IA open source, créé par fabiogra (fabiogra/moseca sur GitHub). Il compte 397 étoiles sur GitHub et 57 forks, il est publié sous la licence MIT et a été mis à jour pour la dernière fois sur GitHub le 28 février 2026.
Separate vocals and instruments in the browser with Demucs.
Decide what you want the project to do before installing anything.
Grab the source and skim the README for setup requirements.
Install dependencies and add any API keys or settings it needs.
Launch it and follow the example workflow from the docs.
A browser-based interface built with Streamlit.
Compose and edit with MIDI workflows.
Faithful ports of published models.
Tweak models and pipelines freely.
Splits songs into vocals, drums, bass, and more.
Describe a track and get audio back.
Download the source and move into the project folder.
git clone https://github.com/fabiogra/moseca.git
cd mosecaCreate a virtual environment and install the requirements.
python3 -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtStart the app or CLI and follow the README examples.
python main.py --helpIt is an open-source project at fabiogra/moseca with 57 forks. Check the repo’s contributors and recent commits to judge how active maintenance is.
Yes. It is MIT licensed, so you can use it commercially with attribution.
Typically 44.1–48kHz stereo — good enough for demos and remixes.
Separation and generation run much faster on GPU, but CPU works for short tracks.
Check the model's license — the code license and model weights may differ.
A resource-efficient music source separation model in PyTorch.
Loss functions for training audio source separation models.
A cross-platform desktop GUI for music source separation.
Separate music tracks into stems in a web app.
Split songs into stems on Apple Silicon with MLX-powered Demucs.
DiffRhythm — blazingly fast, embarrassingly simple full-length song generation with latent diffusion: complete songs with vocals from lyrics and a style prompt, Apache-2.0
Les autres projets de la catégorie Musique IA avec le plus d'étoiles du catalogue LibreAI — la sélection réaliste d'alternatives si moseca ne vous convient pas.
YuE2: frontier music generation with symbolic planning, zero-shot covers, and agentic music editing.
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ACE-Step — the open foundation model for music generation: full songs with vocals and lyrics in 19 languages, up to 4 minutes in about 20 seconds, Apache-2.0
Official DiffSinger code: diffusion-based singing voice synthesis and text-to-speech (AAAI 2022)
Stable Audio Tools — training and inference code for Stability's audio generation models, including Stable Audio Open, MIT
Projets de la catégorie Musique IA proches dans le catalogue, les plus proches en étoiles de moseca — continuez à explorer de part et d'autre.
Local AI song generator with an editable score — YuE2 on your GPU: full songs with vocals, sheet music, covers, exact replay. Native Windows app, no Python, …
Portable AI music generator — full songs with vocals, covers, music videos. One-click install, 100% offline, NVIDIA GPU.
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Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.