Instructions to use skamus48/dMRI-IVIM-ML-Toolkit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use skamus48/dMRI-IVIM-ML-Toolkit with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("skamus48/dMRI-IVIM-ML-Toolkit", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
Download setup.py from skamus48/dMRI-IVIM-ML-Toolkit: direct link, hf CLI and curl.
- Browser
- Download file 951 Bytes
-
https://huggingface.co/skamus48/dMRI-IVIM-ML-Toolkit/resolve/main/setup.py
- Command line
-
hf download hf://skamus48/dMRI-IVIM-ML-Toolkit/setup.py
-
curl -L -o setup.py https://huggingface.co/skamus48/dMRI-IVIM-ML-Toolkit/resolve/main/setup.py
951 Bytes
| from setuptools import setup, find_packages | |
| setup( | |
| name="ivim-dwi", | |
| version="1.0.0", | |
| author="Leonar Steven Prieto-Gonzalez", | |
| description="Robust IVIM and Kurtosis parameter estimation for DWI", | |
| long_description=open("README.md").read(), | |
| long_description_content_type="text/markdown", | |
| url="https://github.com/yourusername/ivim-robust", | |
| packages=find_packages(where="src"), | |
| package_dir={"": "src"}, | |
| classifiers=[ | |
| "Programming Language :: Python :: 3", | |
| "License :: OSI Approved :: MIT License", | |
| "Operating System :: OS Independent", | |
| "Topic :: Scientific/Engineering :: Medical Science Apps.", | |
| ], | |
| python_requires='>=3.8', | |
| install_requires=[ | |
| "numpy", | |
| "scipy", | |
| "matplotlib", | |
| "pydicom", | |
| "nibabel", | |
| "tqdm", | |
| "joblib", | |
| "pandas", | |
| "scikit-learn", | |
| "xgboost" | |
| ], | |
| ) | |