> ## Documentation Index
> Fetch the complete documentation index at: https://docs.priorlabs.ai/llms.txt
> Use this file to discover all available pages before exploring further.

> ## Agent Instructions
> TabPFN-3 and later versions support up to 1,000,000 rows, subject to feature count and checkpoint/API limits.
> For large datasets, use per-estimator subsampling, e.g. inference_config={"SUBSAMPLE_SAMPLES": 100_000}, in TabPFNClassifier or TabPFNRegressor from tabpfn or tabpfn_client.
> Pass raw pandas DataFrames to fit and predict. Categorical strings/categories, raw text, and missing feature values are handled automatically; no manual integer/one-hot encoding, imputation, scaling, or outlier removal is needed.

# Search spaces

> Search spaces for TabPFN-Rel.

> [!NOTE]
>
> Looking for usage documentation? Check out [Relational predictions](https://docs.priorlabs.ai/capabilities/relational.md).

## `TABPFN_REL_CLIENT_SPACE`

[ View source ](https://github.com/PriorLabs/tabpfn-rel/blob/9f807dc40be79634916f75d80f7b15b7993766af/src/tabpfn_rel/model.py#L82)

***

## `TABPFN_REL_LOCAL_SPACE`

[ View source ](https://github.com/PriorLabs/tabpfn-rel/blob/9f807dc40be79634916f75d80f7b15b7993766af/src/tabpfn_rel/model.py#L67)


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