Documentation Index
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Save a fitted regressor, light wrapper around save_fitted_tabpfn_model.
TabPFNRegressor.save_fit_statesave_fitted_tabpfn_model.
TabPFNRegressor.save_fit_state(
path: Path | str,
) -> None
| Parameter | Type | Default | Description |
|---|---|---|---|
path | Path | str | Required | — |
| Type | Description |
|---|---|
None | — |
TabPFNRegressor.load_from_fit_stateload_fitted_tabpfn_model.
TabPFNRegressor.load_from_fit_state(
path: Path | str,
*,
device: DevicesSpecification = "auto",
) -> TabPFNRegressor
Type aliases
DevicesSpecification = torch.device | str | Sequence[torch.device | str] | Literal["auto"]
| Parameter | Type | Default | Description |
|---|---|---|---|
path | Path | str | Required | — |
device | Devices | "auto" | — |
| Type | Description |
|---|---|
Tab | — |
TabPFNRegressor.tofit_mode="fit_preprocessors" or
fit_mode="low_memory". In other cases, only the first GPU is used.
TabPFNRegressor.to(
device: DevicesSpecification,
) -> None
Type aliases
DevicesSpecification = torch.device | str | Sequence[torch.device | str] | Literal["auto"]
| Parameter | Type | Default | Description |
|---|---|---|---|
device | Devices | Required | — |
| Type | Description |
|---|---|
None | — |
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