meta_models

get_single_tabpfn

get_single_tabpfn(config, **kwargs)

Create a single TabPFN model based on the provided configuration.

Parameters:

Name	Type	Description	Default
config		Configuration object with parameters for the TabPFN model	required
**kwargs		Additional keyword arguments to pass to the TabPFN constructor	{}

Returns:

Type	Description
	A TabPFN model (classifier or regressor) configured according to the parameters

get_tabpfn_outer_ensemble

get_tabpfn_outer_ensemble(config: TabPFNConfig, **kwargs)

This will create a model very similar to our standard TabPFN estimators, but it uses multiple model weights to generate predictions. Thus the configs.TabPFNModelPathsConfig can contain multiple paths which are all used.

A product of the preprocessor_trasnforms and paths is created to yield interesting ensemble members.

This only supports multiclass for now. If you want to add regression, you probably want to add the y_transforms to the relevant_config_product. :param config: TabPFNConfig :param kwargs: kwargs are passed to get_single_tabpfn, e.g. device :return: A TabPFNEnsemble, which is a soft voting classifier that mixes multiple standard TabPFN estimators.