Tabular Classification
Scikit-learn
tabular-regression
pokemon
scikit-learn
gradient-boosting
random-forest
kmeans-clustering
feature-engineering
student-project
reichman-university
Eval Results (legacy)
Instructions to use RKugel/pokemon_battle_Dor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use RKugel/pokemon_battle_Dor with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("RKugel/pokemon_battle_Dor", "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

- Xet hash:
- 5d340e46b37cef14d7f5669e1857ff61370f4930837a073a79bf7ffa0483f570
- Size of remote file:
- 153 kB
- SHA256:
- b12359ebee2e44a841919f4904c36f443cb6c9e24bea0de042a56caf2bcc3221
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