Música con IA
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Separate vocals and instruments in the browser with Demucs.
★ 397 estrellasMIT
Ver la guía →pymss es un proyecto de música con IA de código abierto de pymss-project (pymss-project/pymss en GitHub). Tiene 65 estrellas en GitHub y 7 bifurcaciones, se publica bajo la licencia MIT y se actualizó por última vez en GitHub el 26 de septiembre de 2026.
A Python inference package for music source separation models.
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.
Studio-grade sample rates and formats.
Runs on CPU, CUDA, ROCm, Metal, or Vulkan.
Compose and edit with MIDI workflows.
Faithful ports of published models.
Tweak models and pipelines freely.
Splits songs into vocals, drums, bass, and more.
Download the source and move into the project folder.
git clone https://github.com/pymss-project/pymss.git
cd pymssCreate 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 pymss-project/pymss with 7 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.
Separate vocals and instruments in the browser with Demucs.
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.
Friendly front-end for local AI music models, packed with quality-of-life touches.
Run splifft locally: lightweight utilities for music source separation and t.
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Friendly front-end for local AI music models, packed with quality-of-life touches.
Separate music tracks into stems in a web app.
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Gratis y abierto: consigue el código fuente, dale una estrella al repositorio y empieza a crear.