Instructions to use lexandstuff/mlx-demucs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use lexandstuff/mlx-demucs with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir mlx-demucs lexandstuff/mlx-demucs
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
| license: mit | |
| tags: | |
| - mlx | |
| - audio | |
| - source-separation | |
| - music | |
| - apple-silicon | |
| base_model: | |
| - facebook/demucs | |
| library_name: mlx | |
| # MLX Demucs Weights | |
| Converted weights for [mlx-demucs](https://github.com/lextoumbourou/mlx-demucs), an Apple Silicon port of Meta's [Demucs](https://github.com/facebookresearch/demucs) audio source separation models using the [MLX](https://github.com/ml-explore/mlx) framework. | |
| All models achieve <0.04% relative error vs the original PyTorch weights. | |
| ## Models | |
| | 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 | | |
| ## Usage | |
| Install [mlx-demucs](https://github.com/lextoumbourou/mlx-demucs) — weights are downloaded automatically on first use: | |
| ```bash | |
| pip install mlx-demucs | |
| mlx-demucs song.wav | |
| mlx-demucs song.wav -m htdemucs_6s | |
| ``` | |
| Or use the Python API: | |
| ```python | |
| 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) | |
| ``` | |
| ## Performance | |
| ~38x realtime on Apple Silicon. | |
| ## License | |
| Weights are derived from [facebook/demucs](https://github.com/facebookresearch/demucs) and released under the MIT License. Copyright (c) Meta Platforms, Inc. and affiliates. | |