Downloads · 30 days
0
lexandstuff/mlx-demucs
mlx-demucs is a machine learning model from lexandstuff. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for mlx. The card lists the license as mit.
Converted weights for mlx-demucs, an Apple Silicon port of Meta's Demucs audio source separation models using the MLX framework.
Downloads · 30 days
0
Access
Public
Updated May 18, 2026
Repo size
1.2 GB
Likes
0
Public
Click a slice to open those files.
.safetensors1.2 GB · 100%
From the Hugging Face model README
Converted weights for mlx-demucs, an Apple Silicon port of Meta's Demucs audio source separation models using the MLX framework.
All models achieve <0.04% relative error vs the original PyTorch weights.
| Model | Stems | Notes |
|---|---|---|
htdemucs | drums, bass, other, vocals | Hybrid Transformer Demucs |
htdemucs_ft_drums | drums, bass, other, vocals | Fine-tuned for drums |
htdemucs_ft_bass | drums, bass, other, vocals | Fine-tuned for bass |
htdemucs_ft_other | drums, bass, other, vocals | Fine-tuned for other |
htdemucs_ft_vocals | drums, bass, other, vocals | Fine-tuned for vocals |
hdemucs_mmi | drums, bass, other, vocals | Hybrid Demucs, no transformer |
htdemucs_6s | drums, bass, other, vocals, guitar, piano | Experimental 6-stem model |
Install mlx-demucs — weights are downloaded automatically on first use:
pip install mlx-demucs
mlx-demucs song.wav
mlx-demucs song.wav -m htdemucs_6s
Or use the Python API:
from mlx_demucs.utils.loader import load_model
model = load_model("htdemucs") # 4-stem
model = load_model("htdemucs_ft") # 4-stem ensemble (best quality)
model = load_model("htdemucs_6s") # 6-stem (experimental)
~38x realtime on Apple Silicon.
Weights are derived from facebook/demucs and released under the MIT License. Copyright (c) Meta Platforms, Inc. and affiliates.