Instructions to use mgcrea/silhouette-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mgcrea/silhouette-models with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir silhouette-models mgcrea/silhouette-models
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Silhouette models
Background-removal models converted for Silhouette, a Mac app that cuts subjects out of product photos and portraits. Each folder holds one model with its own README (what it is, where the weights come from, what the conversion changed) and the upstream licence, which travels with the files.
| Folder | Model | Format | Licence | Size |
|---|---|---|---|---|
isnet-dis |
IS-Net DIS (general use), Qin et al. 2022 | Core ML .mlpackage, FP16 |
Apache 2.0 | 84 MB |
modnet |
MODNet (photographic portrait matting), Ke et al. 2022 | MLX safetensors, FP32 | Apache 2.0 | 25 MB |
birefnet |
BiRefNet (general), Zheng et al. 2024 | MLX safetensors, FP16 | MIT | 420 MB |
The app downloads these files pinned to a commit and checks each one's size and SHA-256 before using it, so a file here is never changed in place: a new conversion is a new commit. The MLX files hold weights only; the network itself is Swift code in the app.
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Hardware compatibility
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