Instructions to use kushal23/machine-maintenance-predictor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use kushal23/machine-maintenance-predictor with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("kushal23/machine-maintenance-predictor", "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 feature_importance.png from kushal23/machine-maintenance-predictor: direct link, hf CLI and curl.
- Browser
- Download file 57.8 kB
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https://huggingface.co/kushal23/machine-maintenance-predictor/resolve/main/feature_importance.png
- Command line
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hf download hf://kushal23/machine-maintenance-predictor/feature_importance.png
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curl -L -o feature_importance.png https://huggingface.co/kushal23/machine-maintenance-predictor/resolve/main/feature_importance.png
57.8 kB
