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 Magnet_Tc_predictor.joblib
Browse filesThis trained regression model predicts the Curie temperature of the permanent magnets from the chemical composition satisfying the 14:2:1 phase. It has been trained on a specific feature space consisting of 33 elements.
Magnet_Tc_predictor.joblib
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size 76307708
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