Create a Model Group - Amazon SageMaker

Create a Model Group

A Model Group contains different versions of a model. You can create a Model Group that tracks all of the models that you train to solve a particular problem. Create a Model Group by using either the AWS SDK for Python (Boto3) or the Amazon SageMaker Studio console.

Create a Model Group (Boto3)

Important

Custom IAM policies that allow Amazon SageMaker Studio or Amazon SageMaker Studio Classic to create Amazon SageMaker resources must also grant permissions to add tags to those resources. The permission to add tags to resources is required because Studio and Studio Classic automatically tag any resources they create. If an IAM policy allows Studio and Studio Classic to create resources but does not allow tagging, "AccessDenied" errors can occur when trying to create resources. For more information, see Provide permissions for tagging SageMaker resources.

AWS Managed Policies for Amazon SageMaker that give permissions to create SageMaker resources already include permissions to add tags while creating those resources.

To create a Model Group by using Boto3, call the create_model_package_group API operation and specify a name and description as parameters. The following example shows how to create a Model Group. The response from the create_model_package_group call is the Amazon Resource Name (ARN) of the new Model Group.

First, import the required packages and set up the SageMaker Boto3 client.

import time import os from sagemaker import get_execution_role, session import boto3 region = boto3.Session().region_name role = get_execution_role() sm_client = boto3.client('sagemaker', region_name=region)

Now create the Model Group.

import time model_package_group_name = "scikit-iris-detector-" + str(round(time.time())) model_package_group_input_dict = { "ModelPackageGroupName" : model_package_group_name, "ModelPackageGroupDescription" : "Sample model package group" } create_model_package_group_response = sm_client.create_model_package_group(**model_package_group_input_dict) print('ModelPackageGroup Arn : {}'.format(create_model_package_group_response['ModelPackageGroupArn']))

Create a Model Group (Studio or Studio Classic)

To create a Model Group in the Amazon SageMaker Studio console, complete the following steps based on whether you use Studio or Studio Classic.

Studio
  1. Open the SageMaker Studio console by following the instructions in Launch Amazon SageMaker Studio.

  2. In the left navigation pane, choose Models.

  3. Choose the Registered models tab, if not selected already.

  4. Immediately below the Registered models tab label, choose Model Groups, if not selected already.

  5. Choose Register, then choose Model group.

  6. In the Register model group dialog box, enter the following information:

    • The name of the new Model Group in the Model group name field.

    • (Optional) A description for the Model Group in the Description field.

    • (Optional) Any key-value pairs you want to associate with the Model Group in the Tags field. For information about using tags, see Tagging AWS resources in the AWS General Reference.

  7. Choose Register model group.

  8. (Optional) In the Models page, choose the Registered models tab, then choose Model Groups. Confirm your newly-created Model Group appears in the list of Model Groups.

Studio Classic
  1. Sign in to Amazon SageMaker Studio Classic. For more information, see Launch Amazon SageMaker Studio Classic.

  2. In the left navigation pane, choose the Home icon ( Black square icon representing a placeholder or empty image. ).

  3. Choose Models, and then Model registry.

  4. Choose Actions, then choose Create model group.

  5. In the Create model group dialog box, enter the following information:

    • Enter the name of the new Model Group in the Model group name field.

    • (Optional) Enter a description for the Model Group in the Description field.

    • (Optional) Enter any key-value pairs you want to associate with the Model Group in the Tags field. For information about using tags, see Tagging AWS resources in the AWS General Reference.

    • (Optional) Choose a project with which to associate the Model Group in the Project field. For information about projects, see MLOps Automation With SageMaker Projects.

  6. Choose Create model group.