def _create_sagemaker_pipeline_model(self, instance_type):
        """Create a SageMaker Model Entity

        Args:
            instance_type (str): The EC2 instance type that this Model will be used for, this is only
                used to determine if the image needs GPU support or not.
            accelerator_type (str): Type of Elastic Inference accelerator to attach to an endpoint for model loading
                and inference, for example, 'ml.eia1.medium'. If not specified, no Elastic Inference accelerator
                will be attached to the endpoint.
        """
        if not self.sagemaker_session:
            self.sagemaker_session = Session()

        containers = self.pipeline_container_def(instance_type)

        self.name = self.name or name_from_image(containers[0]['Image'])
        self.sagemaker_session.create_model(self.name, self.role, containers, vpc_config=self.vpc_config)
Create a SageMaker Model Entity

        Args:
            instance_type (str): The EC2 instance type that this Model will be used for, this is only
                used to determine if the image needs GPU support or not.
            accelerator_type (str): Type of Elastic Inference accelerator to attach to an endpoint for model loading
                and inference, for example, 'ml.eia1.medium'. If not specified, no Elastic Inference accelerator
                will be attached to the endpoint.