Instructions to use M-Arjun/SpamShield with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use M-Arjun/SpamShield with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("M-Arjun/SpamShield", "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:
- 876b95d211d0a44417258f5dcb967751982787679fb627f0a90b6765a13bcf88
- Size of remote file:
- 56.6 kB
- SHA256:
- 6a260a91f9e0c9af2943d7bc75b5feb656755c6162c41b5620e4ce5867a664aa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.