Instructions to use Centic-AI/kols_recommend_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use Centic-AI/kols_recommend_model with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("Centic-AI/kols_recommend_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 data_cached.pkl from Centic-AI/kols_recommend_model: direct link, hf CLI and curl.
- Browser
- Download file 1.89 MB
-
https://huggingface.co/Centic-AI/kols_recommend_model/resolve/main/data_cached.pkl
- Command line
-
hf download hf://Centic-AI/kols_recommend_model/data_cached.pkl
-
curl -L -o data_cached.pkl https://huggingface.co/Centic-AI/kols_recommend_model/resolve/main/data_cached.pkl
1.89 MB
- Xet hash:
- e902d9d8f0a00343664d81cfcc9bda8846af62e167b0d56534b1141a6a2188b5
- Size of remote file:
- 1.89 MB
- SHA256:
- 7d42c2037247df93b50b3a154f16578093f286262e4fe0f4600a192352229837
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