Instructions to use EngrSamad/LoanDefaulterPredicto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use EngrSamad/LoanDefaulterPredicto with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("EngrSamad/LoanDefaulterPredicto", "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 model_card.json
Browse files- model_card.json +9 -0
model_card.json
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{
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"name": "Nexus Bank Loan Default Prediction Model",
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"description": "A machine learning model to predict loan defaulters for Nexus Bank.",
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"task": "Binary classification",
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"model_type": "K-Nearest Neighbors Classifier",
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"license": "MIT",
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"source": "https://github.com/yourusername/nexus-bank-loan-prediction",
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"tags": ["loan prediction", "binary classification", "machine learning"]
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}
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