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
- Xet hash:
- f171486564a842f6f4a992521997ca90cf9dbe40f2d8a570ab03f1ea52e43f6a
- Size of remote file:
- 937 kB
- SHA256:
- 853b470bff91dbb7b53d04553059dbcc973a6a2e86887b0b53472e59f1665cbf
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