Instructions to use muthuk1/fairrelay-driver-effort with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use muthuk1/fairrelay-driver-effort with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("muthuk1/fairrelay-driver-effort", "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
- Xet hash:
- fd4b04d30e7341759f766e37d8e9b260bf76e8f81f9acf6650686380bad241aa
- Size of remote file:
- 1.37 MB
- SHA256:
- a0dd5da3864a65451f561d717977ea5dd5696af754abcab455c79703f5008a85
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