Image Segmentation
MLX
English
native-mlx
apple-silicon
medical-imaging
mri
brain-tumor
segmentation
research
Instructions to use MedMLX/segresnet-brats-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use MedMLX/segresnet-brats-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download MedMLX/segresnet-brats-mlx --local-dir segresnet-brats-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Pin safetensors-ready runtime and weights
Browse files
README.md
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@@ -37,10 +37,10 @@ Segment brain tumor regions from four MRI sequences with the MONAI SegResNet che
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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
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uv tool install huggingface-hub
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hf download MedMLX/segresnet-brats-mlx --revision
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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 @ git+https://github.com/MedMLX/segresnet-mlx.git@197b670fb805189c1e63dabb10270abac7c08b8b"
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uv tool install huggingface-hub
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hf download MedMLX/segresnet-brats-mlx --revision 14f9cda3649965729663c7365c49fd839c81a01b --local-dir models
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```
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Replace the example input paths with your own files.
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