v6.3.2

Added

• • Moved preprocessing-related code to dedicated modules inside src/tabpfn/preprocessing/
  • Renamed public functions:
    • validate_X_predict → ensure_compatible_predict_input_sklearn
    • validate_Xy_fit → ensure_compatible_fit_inputs_sklearn

  (#720)

• • Add new features to finetuning (metric selection, time limit, passing validation data)
    • Added eval_metric and time_limit parameters to FinetunedTabPFNClassifier and FinetunedTabPFNRegressor
    • Added X_val, y_val parameters to .fit() of FinetunedTabPFNClassifier and FinetunedTabPFNRegressor
  • Fix bug in finetuning for splitting very small datasets
  • Ensure finetuning compares to the default checkpoint and does not accept worse models after finetuning

  (#730)

• • Ensure TabPFNValidationError wraps both custom and sklearn's validate_data() errors (#732)

• Refactor of model encoder. Move imports from tabpfn.architectures.base.encoders to tabpfn.architectures.encoders (#733)

• Renamed the estimator's preprocessor_ attribute to ordinal_encoder_ (#756)