Instructions to use Richsk/a-mim-me-gusta-predictor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use Richsk/a-mim-me-gusta-predictor with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("Richsk/a-mim-me-gusta-predictor", "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:
- 3240ff7f967055dfeda5ed17d925af3a207a99b4429264d36c7ff08215702188
- Size of remote file:
- 63.8 kB
- SHA256:
- 9444bce4da3cb92cc1bffd819051e6474aa206e8ffd7cccd4aca9f789de3f392
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