Música con IA
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Separate vocals and instruments in the browser with Demucs.
★ 397 estrellasMIT
Ver la guía →torch-l1-snr es un proyecto de música con IA de código abierto de crlandsc (crlandsc/torch-l1-snr en GitHub). Tiene 45 estrellas en GitHub y 0 bifurcaciones, se publica bajo la licencia MIT y se actualizó por última vez en GitHub el 1 de septiembre de 2026.
Loss functions for training audio 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.
Splits tracks into isolated stems.
Generate music without cloud APIs.
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.
Download the source and move into the project folder.
git clone https://github.com/crlandsc/torch-l1-snr.git
cd torch-l1-snrCreate 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 crlandsc/torch-l1-snr with 0 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.
A cross-platform desktop GUI for music source separation.
An audio quality metric and loss for training cleaner models.
Stable Audio Tools — training and inference code for Stability's audio generation models, including Stable Audio Open, MIT
A curated MIDI dataset built for training precise music AI models.
Los demás proyectos de Música con IA con más estrellas del catálogo de LibreAI: la lista realista de alternativas si torch-l1-snr no es lo que buscas.
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
Proyectos de Música con IA cercanos en el catálogo, los más próximos en estrellas a torch-l1-snr: sigue explorando a ambos lados.
Rust voice framework: TTS, recognition, and sound in one fast stack.
Open source AI-driven SaaS that generates original music.
Run stemgen-rt locally: stemgenrt is a real-time low-latency music source separ.
Split songs into stems on Apple Silicon with MLX-powered Demucs.
Run splifft locally: lightweight utilities for music source separation and t.
Self-hosted ai music: ai audio engineering system: mcp server + claude code s.
Gratis y abierto: consigue el código fuente, dale una estrella al repositorio y empieza a crear.