ModelPackage
import type { ModelPackage } from "https://aws-api.deno.dev/v0.3/services/sagemaker.ts?docs=full";
A versioned model that can be deployed for SageMaker inference.
§Properties
An array of additional Inference Specification objects.
Whether the model package is to be certified to be listed on Amazon Web Services Marketplace. For information about listing model packages on Amazon Web Services Marketplace, see List Your Algorithm or Model Package on Amazon Web Services Marketplace.
The metadata properties for the model package.
The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
Represents the drift check baselines that can be used when the model monitor is set using the model package.
The approval status of the model. This can be one of the following values.
APPROVED
- The model is approvedREJECTED
- The model is rejected.PENDING_MANUAL_APPROVAL
- The model is waiting for manual approval.
Metrics for the model.
The status of the model package. This can be one of the following values.
PENDING
- The model package is pending being created.IN_PROGRESS
- The model package is in the process of being created.COMPLETED
- The model package was successfully created.FAILED
- The model package failed.DELETING
- The model package is in the process of being deleted.
The Amazon Simple Storage Service path where the sample payload are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
A list of the tags associated with the model package. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.