Instructions to use Zipeng365/WISP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use Zipeng365/WISP with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("Zipeng365/WISP", "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 src/wisp_release/__init__.py from Zipeng365/WISP: direct link, hf CLI and curl.
- Browser
- Download file 321 Bytes
-
https://huggingface.co/Zipeng365/WISP/resolve/main/src/wisp_release/__init__.py
- Command line
-
hf download hf://Zipeng365/WISP/src/wisp_release/__init__.py
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curl -L -o __init__.py https://huggingface.co/Zipeng365/WISP/resolve/main/src/wisp_release/__init__.py
321 Bytes
| """Small release interfaces for WISP; importing this package performs no work.""" | |
| from .checkpoints import load_checkpoint, predict_checkpoint | |
| from .methods import list_methods | |
| from .selection import fit_selector | |
| __all__ = ["load_checkpoint", "predict_checkpoint", "list_methods", "fit_selector"] | |
| __version__ = "0.1.0" | |