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
Card: add quick start
Browse files
README.md
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The weights were converted from the [official TotalSegmentator v2.0.0 weight archives](https://github.com/wasserth/TotalSegmentator/releases/tag/v2.0.0-weights) for use with [totalsegmentator-mlx](https://github.com/MedMLX/totalsegmentator-mlx). Conversion changes tensor names and layouts for MLX; the models were not retrained.
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```bash
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uv pip install \
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"nnunet-mlx>=0.6.4" \
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"totalsegmentator-mlx>=0.1.6" \
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The weights were converted from the [official TotalSegmentator v2.0.0 weight archives](https://github.com/wasserth/TotalSegmentator/releases/tag/v2.0.0-weights) for use with [totalsegmentator-mlx](https://github.com/MedMLX/totalsegmentator-mlx). Conversion changes tensor names and layouts for MLX; the models were not retrained.
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## Quick start
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```bash
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uv venv --python 3.13
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source .venv/bin/activate
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uv pip install \
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"nnunet-mlx>=0.6.4" \
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"totalsegmentator-mlx>=0.1.6" \
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