SageMaker Model Package

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An AWS SageMaker Model Package is a container for machine learning models that includes model artifacts, inference code, and metadata. It enables versioning, sharing, and deployment of models across different environments. Model packages can be created, validated, and stored in the SageMaker Model Registry, making it easier to manage the lifecycle of ML models and ensure consistent deployment.

aws.sagemaker_model_package

Fields

ID	Type	Data Type	Description
_key	core	string
account_id	core	string
additional_inference_specifications	core	json	An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
approval_description	core	string	A description provided for the model approval.
certify_for_marketplace	core	bool	Whether the model package is certified for listing on Amazon Web Services Marketplace.
created_by	core	json	Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
creation_time	core	timestamp	A timestamp specifying when the model package was created.
customer_metadata_properties	core	hstore	The metadata properties associated with the model package versions.
domain	core	string	The machine learning domain of the model package you specified. Common machine learning domains include computer vision and natural language processing.
drift_check_baselines	core	json	Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.
inference_specification	core	json	Details about inference jobs that you can run with models based on this model package.
last_modified_by	core	json	Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
last_modified_time	core	timestamp	The last time that the model package was modified.
metadata_properties	core	json	Metadata properties of the tracking entity, trial, or trial component.
model_approval_status	core	string	The approval status of the model package.
model_card	core	json	The model card associated with the model package. Since ModelPackageModelCard is tied to a model package, it is a specific usage of a model card and its schema is simplified compared to the schema of ModelCard. The ModelPackageModelCard schema does not include model_package_details, and model_overview is composed of the model_creator and model_artifact properties. For more information about the model package model card schema, see Model package model card schema. For more information about the model card associated with the model package, see View the Details of a Model Version.
model_life_cycle	core	json	A structure describing the current state of the model in its life cycle.
model_metrics	core	json	Metrics for the model.
model_package_arn	core	string	The Amazon Resource Name (ARN) of the model package.
model_package_description	core	string	A brief summary of the model package.
model_package_group_name	core	string	If the model is a versioned model, the name of the model group that the versioned model belongs to.
model_package_name	core	string	The name of the model package being described.
model_package_status	core	string	The current status of the model package.
model_package_status_details	core	json	Details about the current status of the model package.
model_package_version	core	int64	The version of the model package.
sample_payload_url	core	string	The Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path points to a single gzip compressed tar archive (.tar.gz suffix).
security_config	core	json	The KMS Key ID (KMSKeyId) used for encryption of model package information.
skip_model_validation	core	string	Indicates if you want to skip model validation.
source_algorithm_specification	core	json	Details about the algorithm that was used to create the model package.
source_uri	core	string	The URI of the source for the model package.
tags	core	hstore
task	core	string	The machine learning task you specified that your model package accomplishes. Common machine learning tasks include object detection and image classification.
validation_specification	core	json	Configurations for one or more transform jobs that SageMaker runs to test the model package.