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
| { | |
| "model_type": "sklearn", | |
| "model_file": "spam_detector_model_v2.pkl", | |
| "dependencies": { | |
| "scikit-learn": "1.5.1", | |
| "joblib": "latest" | |
| }, | |
| "task": "text-classification", | |
| "input_example": "This is an example text input.", | |
| "output_example": "spam" | |
| } | |