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
Download 300/dataset.json from MedMLX/totalsegmentator-mlx: direct link, hf CLI and curl.
- Browser
- Download file 406 Bytes
-
https://huggingface.co/MedMLX/totalsegmentator-mlx/resolve/main/300/dataset.json
- Command line
-
hf download hf://MedMLX/totalsegmentator-mlx/300/dataset.json
-
curl -L -o dataset.json https://huggingface.co/MedMLX/totalsegmentator-mlx/resolve/main/300/dataset.json
406 Bytes
| { | |
| "name": "Segmentation of X", | |
| "description": "Segmentation", | |
| "reference": "Jakob", | |
| "licence": "-", | |
| "release": "0.0", | |
| "labels": { | |
| "background": 0, | |
| "body_trunc": 1, | |
| "body_extremities": 2 | |
| }, | |
| "numTraining": 1559, | |
| "channel_names": { | |
| "0": "CT" | |
| }, | |
| "file_ending": ".nii.gz", | |
| "overwrite_image_reader_writer": "NibabelIOWithReorient" | |
| } |