TimeSeriesFoundationModel¶

class autogluon.cloud.TimeSeriesFoundationModel(model_id: str, **kwargs)[source]¶

Foundation model for time series forecasting (Chronos, etc.).

Parameters:

model_id – ID of the foundation model from the model registry.
backend – Cloud backend to use.
cloud_output_path –
S3 location where intermediate artifacts are stored. Accepts:
- s3://bucket — a unique timestamped subfolder ag-<timestamp> is appended.
- s3://bucket/prefix — used verbatim. Re-running with the same prefix will overwrite previously written artifacts.
- None (default) — use the bucket saved in ~/.autogluon/cloud.yaml (set by autogluon.cloud.bootstrap() / autogluon.cloud.register()) and append a timestamped subfolder. Raises if no bucket is configured.
hyperparameters – Default hyperparameters applied to inference and (when supported) training.
role – ARN of the SageMaker execution role used to run training and inference jobs. If None, falls back to role_arn in ~/.autogluon/cloud.yaml (set by autogluon.cloud.bootstrap() / autogluon.cloud.register()), and finally to sagemaker.get_execution_role().

Methods

`deploy`	Deploy model to a real-time endpoint.
`predict`	Run batch prediction for time series.