Instructions to use carineRam/wine_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use carineRam/wine_model with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("carineRam/wine_model", "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 inference.py from carineRam/wine_model: direct link, hf CLI and curl.
- Browser
- Download file 209 Bytes
-
https://huggingface.co/carineRam/wine_model/resolve/main/inference.py
- Command line
-
hf download hf://carineRam/wine_model/inference.py
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curl -L -o inference.py https://huggingface.co/carineRam/wine_model/resolve/main/inference.py
209 Bytes
| def model_fn(model_dir): | |
| import joblib | |
| import os | |
| return joblib.load(os.path.join(model_dir, "sklearn_model.joblib")) | |
| def predict_fn(input_data, model): | |
| return model.predict(input_data) | |