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
Update README.md
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README.md
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- ar
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- hi
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pipeline_tag: text-classification
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library_name: sklearn
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tags:
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- Spam
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- Spam-Categoriser
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---
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# SpamShield: Multilingual Spam Detection & Category Classification
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If you find SpamShield helpful, please give it a ⭐ on [Hugging Face](https://huggingface.co/M-Arjun/SpamShield)!
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pipeline_tag: text-classification
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library_name: sklearn
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tags:
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- Spam
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- Spam-Categoriser
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datasets:
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- M-Arjun/SpamShield-Datasets
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new_version: M-Arjun/SpamShield
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---
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# SpamShield: Multilingual Spam Detection & Category Classification
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If you find SpamShield helpful, please give it a ⭐ on [Hugging Face](https://huggingface.co/M-Arjun/SpamShield)!
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</div>
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