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
Version 1: LogisticRegression baseline (C=1.0)
Browse files
README.md
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---
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tags:
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- sklearn
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- mlops-demo
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---
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# Modele de versioning demo - v1
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LogisticRegression entrainee sur le dataset Iris.
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- Accuracy (test) : 1.0000
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- Hyperparametres : C=1.0, max_iter=200
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