Instructions to use SharleyK/predictive-maintenance-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use SharleyK/predictive-maintenance-model with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("SharleyK/predictive-maintenance-model", "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
| { | |
| "model_name": "AdaBoost", | |
| "parameters": { | |
| "learning_rate": 0.05, | |
| "n_estimators": 100 | |
| }, | |
| "performance": { | |
| "test_accuracy": 0.6667519836191451, | |
| "test_precision": 0.6854040242733951, | |
| "test_recall": 0.8712951684937068, | |
| "test_f1": 0.7672506256703611, | |
| "test_roc_auc": 0.6959420475671518 | |
| }, | |
| "training_date": "2026-02-08 16:01:01", | |
| "feature_count": 17, | |
| "training_samples": 15628, | |
| "test_samples": 3907 | |
| } |