deploy¶
- TimeSeriesFoundationModel.deploy(instance_type: str | None = None, endpoint_name: str | None = None, hyperparameters: Dict[str, Any] | None = None, framework_version: str = 'latest', custom_image_uri: str | None = None, wait: bool = True, **backend_kwargs) TimeSeriesEndpoint[source]¶
Deploy model to a real-time endpoint.
- Parameters:
instance_type – Instance type for the endpoint. If None, will use the default from the model registry.
endpoint_name – Custom endpoint name. If None, will auto-generate a unique name.
hyperparameters – Model hyperparameters for inference. Overrides values passed to the constructor.
framework_version – Container framework version. If ‘latest’, uses the most recent available.
custom_image_uri – Custom Docker image URI for the inference container.
wait – Whether to block until the endpoint is ready.
**backend_kwargs – Backend-specific arguments (e.g., initial_instance_count, volume_size, model_kwargs, deploy_kwargs).
- Return type: