Posted On: Jul 5, 2023
Today, we are excited to announce the integration of Amazon SageMaker Model Cards and Amazon SageMaker Model Registry, allowing you to associate a SageMaker Model Card with a specific model version in SageMaker Model Registry. This enables you to establish a single source of truth for your registered model versions, with comprehensive, centralized, and standardized documentation across all stages of the model’s journey on SageMaker, facilitating discoverability and promoting governance, compliance, and accountability throughout the model lifecycle.
Amazon SageMaker Model Registry helps you centrally manage your machine learning (ML) models. Amazon SageMaker Model Cards enables you to document critical details about your models in a single place for streamlined governance and reporting, including the model's intended uses, your risk rating, and performance goals. Furthermore, available model metadata is auto-populated in the associated SageMaker Model Card. For example, when you associate a SageMaker Model Card with a registered model version in SageMaker Model Registry, the system automatically pulls information such as training details, evaluation results, source algorithms, inference specification, and model approval status from SageMaker Model Registry and surfaces it in the SageMaker Model Card.
Amazon SageMaker Model Cards is available in all Amazon Web Services regions where Amazon SageMaker is currently available, except the GovCloud (US) regions.
To get started, associate a model card to a model package version via the Amazon SageMaker Python SDK. Visit the Amazon SageMaker developer guide for information on SageMaker Model Cards, and ML Governance to learn more about ML Governance with Amazon SageMaker.