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
| { | |
| "spam_threshold": 0.4941, | |
| "short_text_word_count": 2, | |
| "short_text_threshold": 0.9, | |
| "very_short_text_word_count": 1, | |
| "very_short_text_threshold": 0.96, | |
| "target_min_precision": 0.98, | |
| "vectorizer": "tfidf_word_char", | |
| "word_max_features": 10000, | |
| "char_max_features": 5000, | |
| "min_df": 3 | |
| } |