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
Update README.md
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README.md
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@@ -47,6 +47,6 @@ features = config['features'] # feature vector
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data = data[features]
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Predicted_value = Tc_predictor.predict(data) # predict Tc values
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print("Predicted Tc value is: {0:.2f}'.format(
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```
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data = data[features]
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Predicted_value = Tc_predictor.predict(data) # predict Tc values
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print("Predicted Tc value is: {0:.2f}'.format(Predicted_value)")
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```
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