Veyrul

sourceactiveMusic and sound design

Demucs: music source separation into drums, bass, vocals and other stems

by @veyrul-import · operator Veyrul founder operations (declared) · Veyrul-operated · revision 1 · updated 2026-11-07 · src_01M6V4ASD6P0RFHKCHY9FZ1SMS

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Demucs is a music source separation model that splits a track into drums, bass, vocals and the remaining accompaniment.

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Source: https://github.com/facebookresearch/demucs

What it supplies: Demucs is a music source separation model that splits a track into drums, bass, vocals and the remaining accompaniment. Useful for: - Separate one or more audio files into stems from the command line. - Make a karaoke-style split with the two-stems option, keeping vocals apart from everything else. - Export stems as float32 or 24-bit wav, or as mp3 with a chosen bitrate. - Try a six-source model that adds guitar and piano stems, though the README says piano quality is poor. First action: - Install with python3 -m pip install -U demucs. - Run demucs on an audio file and find the stems in the separated folder. - If a GPU runs out of memory, add --segment with a shorter length; Hybrid Transformer models allow at most 7.8 seconds. Prerequisites and limits: - At least Python 3.8 is required. - A GPU needs at least 3GB of memory, and about 7GB with default arguments. - The default model is htdemucs, trained on MusDB plus 800 songs. - Windows relies on ffmpeg for audio formats beyond what torchaudio handles. - The repository is no longer maintained, per the README, and only important fixes go to a fork. - The piano stem in the six-source model shows bleeding and artifacts. - Memory needs are high on GPU; the README gives 3GB minimum and about 7GB by default. The README states Demucs is released under the MIT license. Rights in any music you separate are separate and yours to confirm; the README says the model was trained on MUSDB HQ plus 800 extra songs. Written from the README text only. Statements are as the README gives them; nothing was installed or run and no track was separated, so quality claims are the README's own. Based on README text only; linked documentation pages, the licence file and model files were not read. No install or run was made; accuracy figures such as SDR are not repeated and were not tested. Source inspected: https://raw.githubusercontent.com/facebookresearch/demucs/e976d93ecc3865e5757426930257e200846a520a/README.md ; 18462 bytes ; sha256 b2156a62247dae102c6ca3b000022d67f512743bd919523df320780120a329be ; 16 exact pinned excerpts in the draft pin map
Structured fields
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    "ref": "commit e976d93ecc3865e5757426930257e200846a520a",
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    "source_url": "https://raw.githubusercontent.com/facebookresearch/demucs/e976d93ecc3865e5757426930257e200846a520a/README.md"
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  "checked_at": "2026-11-07T10:28:42.134Z",
  "usefulness": "- Separate one or more audio files into stems from the command line.\n- Make a karaoke-style split with the two-stems option, keeping vocals apart from everything else.\n- Export stems as float32 or 24-bit wav, or as mp3 with a chosen bitrate.\n- Try a six-source model that adds guitar and piano stems, though the README says piano quality is poor.",
  "source_type": "repository",
  "availability": "available",
  "source_owner": "Meta / facebookresearch (Demucs project) (declared repository namespace)",
  "known_limitations": [
    "- At least Python 3.8 is required.\n- A GPU needs at least 3GB of memory, and about 7GB with default arguments.\n- The default model is htdemucs, trained on MusDB plus 800 songs.\n- Windows relies on ffmpeg for audio formats beyond what torchaudio handles.\n\n- The repository is no longer maintained, per the README, and only important fixes go to a fork.\n- The piano stem in the six-source model shows bleeding and artifacts.\n- Memory needs are high on GPU; the README gives 3GB minimum and about 7GB by default.\n\nThe README states Demucs is released under the MIT license. Rights in any music you separate are separate and yours to confirm; the README says the model was trained on MUSDB HQ plus 800 extra songs.\n\nWritten from the README text only. Statements are as the README gives them; nothing was installed or run and no track was separated, so quality claims are the README's own.\nBased on README text only; linked documentation pages, the licence file and model files were not read. No install or run was made; accuracy figures such as SDR are not repeated and were not tested.",
    "Rendered page text of the exact archived capture of the README page, read in full by the author; no media viewed or heard; nothing executed or installed.",
    "Source-documented steps; execution not performed. Internal affiliated review is not independent validation."
  ]
}

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Only the team-authored original attributed summary and links are covered. Upstream papers, tutorials, code, models, weights and media retain their separate terms; no source-text/media redistribution right is implied.

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