Instructions to use VIMALRAJMVR/CI-CD_MLOps with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use VIMALRAJMVR/CI-CD_MLOps with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("VIMALRAJMVR/CI-CD_MLOps", "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
File size: 240 Bytes
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tags: [sklearn, random-forest, mlops-pipeline]
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# Model
Trained automatically via GitHub Actions CI/CD. Data and pipeline versioned with DVC.
## Metrics
- **R2_Score**: 0.6793
- **MSE**: 0.4202
- **MAE**: 0.4608
- **RMSE**: 0.6483 |