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
| tags: [sklearn, random-forest, mlops-pipeline] | |
| # 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 |