Instructions to use MedMLX/totalsegmentator-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use MedMLX/totalsegmentator-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download MedMLX/totalsegmentator-mlx --local-dir totalsegmentator-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
TotalSegmentator v2 CT for MLX
Native MLX safetensors for TotalSegmentator v2 CT inference on Apple Silicon. The five 1.5 mm standard models are in 291β295, the 3 mm fast model in 297, the 6 mm coarse model in 298, and the body crop model in 300. Each folder includes nnU-Net plans and model metadata.
The weights were converted from the official TotalSegmentator v2.0.0 weight archives for use with totalsegmentator-mlx. Conversion changes tensor names and layouts for MLX; the models were not retrained.
uv pip install \
"nnunet-mlx>=0.6.1" \
"totalsegmentator-mlx>=0.1.4" \
huggingface-hub
hf download MedMLX/totalsegmentator-mlx --revision 6c03d6f90ccf53f224c3985cbdecf1eaa96555af --local-dir models
totalsegmentator-mlx predict -i ct.nii.gz -o mask.nii.gz --model-dir models
The total and body tasks are distributed by the authors under Apache-2.0. See the upstream repository and the included license for terms and attribution. Please cite TotalSegmentator and nnU-Net as described by the upstream authors. For research and education; outputs require human review.
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