Tabular Regression
Scikit-learn
Joblib
Voting_regressor
materials property prediction
baseline-trainer
Instructions to use IMFAA/Magnet_Tc_predictor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use IMFAA/Magnet_Tc_predictor with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("IMFAA/Magnet_Tc_predictor", "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
Upload config.json
Browse files- config.json +1 -0
config.json
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{"features": ["Sc", "Ti", "V", "Cr", "Mn", "Fe", "Co", "Ni", "Cu", "Al", "Si", "Ga", "Ge", "Be", "Nb", "Mo", "Re", "Ru", "La", "Ce", "Pr", "Nd", "Sm", "Eu", "Gd", "Tb", "Dy", "Ho", "Er", "Tm", "Yb", "Lu", "Th", "Y", "Zr", "B", "C"], "targets": ["target"], "model_type": "Voting_regressor", "target_mapping": {}}
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