Image Segmentation
MLX
English
native-mlx
apple-silicon
medical-imaging
ct
kidney
segmentation
research
Instructions to use MedMLX/segresnet-renal-cect-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use MedMLX/segresnet-renal-cect-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download MedMLX/segresnet-renal-cect-mlx --local-dir segresnet-renal-cect-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Update model card installation instructions
Browse files
README.md
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@@ -37,12 +37,10 @@ Segment renal structures from three-phase contrast-enhanced CT with native MLX.
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uv venv --python 3.13
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source .venv/bin/activate
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release="$repo/releases/download/v0.2.1"
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uv pip install "$release/segresnet_mlx-0.2.1-py3-none-any.whl"
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uv tool install huggingface-hub
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hf download MedMLX/segresnet-renal-cect-mlx --local-dir models
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```
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Replace the example input paths with your own files.
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uv venv --python 3.13
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source .venv/bin/activate
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uv pip install "segresnet-mlx==0.2.2"
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uv tool install huggingface-hub
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hf download MedMLX/segresnet-renal-cect-mlx --revision 6d9f11e631c3c6b8e878f791687ed989f3ab4caf --local-dir models
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```
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Replace the example input paths with your own files.
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