Instructions to use Devanapally/FraudShield-ULB-Card with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use Devanapally/FraudShield-ULB-Card with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("Devanapally/FraudShield-ULB-Card", "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 model-2.joblib from Devanapally/FraudShield-ULB-Card: direct link, hf CLI and curl.
- Browser
- Download file 1.99 MB
-
https://huggingface.co/Devanapally/FraudShield-ULB-Card/resolve/main/model-2.joblib
- Command line
-
hf download hf://Devanapally/FraudShield-ULB-Card/model-2.joblib
-
curl -L -o model-2.joblib https://huggingface.co/Devanapally/FraudShield-ULB-Card/resolve/main/model-2.joblib
1.99 MB
- Xet hash:
- 23707731cfb415f92d998857cbbfa8511d3029399215655aee81f45e561ff55d
- Size of remote file:
- 1.99 MB
- SHA256:
- c5dc975d98a8c4e017931e8451c7720e230fac8950bee8635813bd3c058a5a0c
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