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SageMaker Model Registry can be used to catalog and manage different model versions. model_group_name can't be used directly from Sagemaker Model Registry. First you need to deploy the model. After deploying the model, Endpoint would be created. Then you can directly invoke the Endpoint API.
Generally at first Model You need to to create a Model group[1] << Register a Model Version using Sagemaker Model registry [2] << Update the Approval Status of a Model to approved[3] << Deploy the Model for registry[4] << Invoke the Endpoint API.
Kindly go through the below example of deploying the model and then invoking it via Endpoint API https://github.com/aws/amazon-sagemaker-examples/blob/main/serverless-inference/serverless-model-registry.ipynb
[1] https://docs.aws.amazon.com/sagemaker/latest/dg/model-registry-model-group.html [2] https://docs.aws.amazon.com/sagemaker/latest/dg/model-registry-version.html [3] https://docs.aws.amazon.com/sagemaker/latest/dg/model-registry-approve.html [4] https://docs.aws.amazon.com/sagemaker/latest/dg/model-registry-deploy.html
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A model registry in SageMaker is a catalog of models. If you'd like to predict without deploying the model, I believe the way would be to download the model from the model registry's S3 location, load the model and then predict.