Instructions to use quantumbit/spam-comment-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use quantumbit/spam-comment-detector with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("quantumbit/spam-comment-detector", "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
Create config.json
Browse files- config.json +11 -0
config.json
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{
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"model_type": "sklearn",
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"model_file": "spam_detector_model_v2.pkl",
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"dependencies": {
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"scikit-learn": "1.5.1",
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"joblib": "latest"
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},
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"task": "text-classification",
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"input_example": "This is an example text input.",
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"output_example": "spam"
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}
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