predict¶

TabularEndpoint.predict(data: str | Path | DataFrame, train_data: str | Path | DataFrame, label: str, **inference_kwargs: Any) → Series[source]¶

Fit the foundation model on train_data and predict data.

The serialized request includes both train_data and data and must not exceed SageMaker’s 6 MiB real-time invocation payload limit. Use autogluon.cloud.TabularFoundationModel.predict() for larger inputs.