Instructions to use rawqubit/ClassicML-Prompt-Injection-Detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use rawqubit/ClassicML-Prompt-Injection-Detector with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("rawqubit/ClassicML-Prompt-Injection-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
Download sklearn_model.joblib from rawqubit/ClassicML-Prompt-Injection-Detector: direct link, hf CLI and curl.
- Browser
- Download file 9.25 kB
-
https://huggingface.co/rawqubit/ClassicML-Prompt-Injection-Detector/resolve/main/sklearn_model.joblib
- Command line
-
hf download hf://rawqubit/ClassicML-Prompt-Injection-Detector/sklearn_model.joblib
-
curl -L -o sklearn_model.joblib https://huggingface.co/rawqubit/ClassicML-Prompt-Injection-Detector/resolve/main/sklearn_model.joblib
9.25 kB
- Xet hash:
- 85871cac4969e6c0eff650be821839dc977952e77e5947ef555349db19d21c6b
- Size of remote file:
- 9.25 kB
- SHA256:
- eb1ad3d085cdb02aab44bdfb8bdbd9dde9ed218c2187e89aa53b22a2e1b685b1
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