{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/5"},{"label":"Sound/Audio","url":"https://skillfed.io/packages/category/multimedia-sound-audio"}],"enrichment":{"capability":"Demucs separates music into individual stems\u2014drums, bass, vocals, and accompaniment\u2014using a hybrid transformer-based neural network trained on waveform and spectrogram domains.","skillfed_tags":["audio-processing","music-analysis","neural-networks"],"use_cases":["Extract vocals from a song for karaoke or vocal-focused remixing workflows.","Isolate drum and bass tracks for beat analysis, re-arrangement, or music production.","Create instrumental versions by removing vocals for background music or licensing.","Prepare training data for music information retrieval or other audio ML tasks.","Analyze song composition by examining separated stems independently."],"what_it_does":"Demucs is a music source separation model that breaks a single audio track into isolated stems\u2014drums, bass, vocals, and other accompaniment. Version 4 uses a hybrid transformer architecture that processes both waveform and spectrogram representations simultaneously, achieving state-of-the-art separation quality (9.0 dB SDR on the MUSDB HQ test set). The model was trained on MUSDB HQ plus 800 additional songs.\n\nYou invoke it via command-line or Python API to process MP3, WAV, or other audio formats. It outputs separate audio files for each stem. The package includes multiple model variants: htdemucs_ft (fine-tuned, recommended), htdemucs (baseline), hdemucs_mmi (retrained), and an experimental 6-source model. Separation runs on CPU or GPU; GPU is significantly faster but not required.","worth_installing":"Yes. Demucs is actively maintained, has no known vulnerabilities, low install friction, and permissive licensing. It delivers state-of-the-art stem separation out of the box. Install if you need to separate music into drums, bass, vocals, or other stems; skip if you only need metadata extraction or don't work with audio."},"id":"demucs","links":{"html":"https://skillfed.io/packages/demucs","md":"https://skillfed.io/packages/demucs.md","pypi":"https://pypi.org/project/demucs/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-11","license_spdx":null,"license_treatment":"permissive","name":"demucs","python_support":"supports_current","summary":"Music source separation in the waveform domain."},"popularity":{"monthly_downloads":400505,"position":6939,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"4.1.0"}