Instructions to use MathisKhan/mlops-versioning-demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use MathisKhan/mlops-versioning-demo with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("MathisKhan/mlops-versioning-demo", "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 model.joblib from MathisKhan/mlops-versioning-demo: direct link, hf CLI and curl.
- Browser
- Download file 991 Bytes
-
https://huggingface.co/MathisKhan/mlops-versioning-demo/resolve/main/model.joblib
- Command line
-
hf download hf://MathisKhan/mlops-versioning-demo/model.joblib
-
curl -L -o model.joblib https://huggingface.co/MathisKhan/mlops-versioning-demo/resolve/main/model.joblib
991 Bytes
- Xet hash:
- 01cdd206e13751a35f6cd2fa31de5df356628f8dcac352fe30ee1ef6691766d5
- Size of remote file:
- 991 Bytes
- SHA256:
- 006810b7c392eb79ecb4ce17bf704912945e916ffeb5a94054012ef20352aac2
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