facebookresearch/demucs

Health v2 · maintenance only

Flags: no_releases archived

Adoption not part of the score

10359 stars · 1586 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Demucs is a state-of-the-art music source separation model from Meta AI that splits songs into stems like drums, bass, and vocals using a hybrid spectrogram/waveform architecture with Transformers. This original repository is no longer maintained; development continues in a fork at github.com/adefossez/demucs.

Use cases

• separate vocals from a song
• extract drums and bass stems from music
• remove vocals to make a karaoke track
• split a music track into individual instrument stems
• run music source separation on audio files
• research hybrid spectrogram and waveform separation models

When to choose

• you need high-quality stem separation of vocals, drums, and bass from songs
• you want a proven, widely used open-source separation model with pretrained weights
• you are doing audio research and want a reference implementation of hybrid separation models

When to avoid

• you need active maintenance or new features - use the adefossez/demucs fork instead
• you need the sparse attention model from the paper, which is not released
• you need real-time separation on low-resource hardware without a GPU

Facets

library · maturity maintenance

machine-learning audio-processing deep-learning machine-learning deep-learning media python cross-platform music-source-separation stem-separation audio u-net transformer facebook-research vocal-removal gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="facebookresearch/demucs")