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:
- a936f3396e2d2e40093340e21aa2c88b94fbd995f33e04271ab531f0fc73028c
- Size of remote file:
- 556 kB
- SHA256:
- c553ddfc584339f888e0a001031a52cd6fa287ad013e2c4e05cd715287bea0c9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.