src/sagemaker/huggingface/model.py [170:230]:
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            model_data, image_uri, role, entry_point, predictor_cls=predictor_cls, **kwargs
        )

        self.model_server_workers = model_server_workers

    def register(
        self,
        content_types,
        response_types,
        inference_instances,
        transform_instances,
        model_package_name=None,
        model_package_group_name=None,
        image_uri=None,
        model_metrics=None,
        metadata_properties=None,
        marketplace_cert=False,
        approval_status=None,
        description=None,
        drift_check_baselines=None,
    ):
        """Creates a model package for creating SageMaker models or listing on Marketplace.

        Args:
            content_types (list): The supported MIME types for the input data.
            response_types (list): The supported MIME types for the output data.
            inference_instances (list): A list of the instance types that are used to
                generate inferences in real-time.
            transform_instances (list): A list of the instance types on which a transformation
                job can be run or on which an endpoint can be deployed.
            model_package_name (str): Model Package name, exclusive to `model_package_group_name`,
                using `model_package_name` makes the Model Package un-versioned.
                Defaults to ``None``.
            model_package_group_name (str): Model Package Group name, exclusive to
                `model_package_name`, using `model_package_group_name` makes the Model Package
                versioned. Defaults to ``None``.
            image_uri (str): Inference image URI for the container. Model class' self.image will
                be used if it is None. Defaults to ``None``.
            model_metrics (ModelMetrics): ModelMetrics object. Defaults to ``None``.
            metadata_properties (MetadataProperties): MetadataProperties object.
                Defaults to ``None``.
            marketplace_cert (bool): A boolean value indicating if the Model Package is certified
                for AWS Marketplace. Defaults to ``False``.
            approval_status (str): Model Approval Status, values can be "Approved", "Rejected",
                or "PendingManualApproval". Defaults to ``PendingManualApproval``.
            description (str): Model Package description. Defaults to ``None``.
            drift_check_baselines (DriftCheckBaselines): DriftCheckBaselines object (default: None).

        Returns:
            A `sagemaker.model.ModelPackage` instance.
        """
        instance_type = inference_instances[0]
        self._init_sagemaker_session_if_does_not_exist(instance_type)

        if image_uri:
            self.image_uri = image_uri
        if not self.image_uri:
            self.image_uri = self.serving_image_uri(
                region_name=self.sagemaker_session.boto_session.region_name,
                instance_type=instance_type,
            )
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src/sagemaker/pytorch/model.py [140:198]:
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            model_data, image_uri, role, entry_point, predictor_cls=predictor_cls, **kwargs
        )

        self.model_server_workers = model_server_workers

    def register(
        self,
        content_types,
        response_types,
        inference_instances,
        transform_instances,
        model_package_name=None,
        model_package_group_name=None,
        image_uri=None,
        model_metrics=None,
        metadata_properties=None,
        marketplace_cert=False,
        approval_status=None,
        description=None,
        drift_check_baselines=None,
    ):
        """Creates a model package for creating SageMaker models or listing on Marketplace.

        Args:
            content_types (list): The supported MIME types for the input data.
            response_types (list): The supported MIME types for the output data.
            inference_instances (list): A list of the instance types that are used to
                generate inferences in real-time.
            transform_instances (list): A list of the instance types on which a transformation
                job can be run or on which an endpoint can be deployed.
            model_package_name (str): Model Package name, exclusive to `model_package_group_name`,
                using `model_package_name` makes the Model Package un-versioned (default: None).
            model_package_group_name (str): Model Package Group name, exclusive to
                `model_package_name`, using `model_package_group_name` makes the Model Package
                versioned (default: None).
            image_uri (str): Inference image uri for the container. Model class' self.image will
                be used if it is None (default: None).
            model_metrics (ModelMetrics): ModelMetrics object (default: None).
            metadata_properties (MetadataProperties): MetadataProperties object (default: None).
            marketplace_cert (bool): A boolean value indicating if the Model Package is certified
                for AWS Marketplace (default: False).
            approval_status (str): Model Approval Status, values can be "Approved", "Rejected",
                or "PendingManualApproval" (default: "PendingManualApproval").
            description (str): Model Package description (default: None).
            drift_check_baselines (DriftCheckBaselines): DriftCheckBaselines object (default: None).

        Returns:
            A `sagemaker.model.ModelPackage` instance.
        """
        instance_type = inference_instances[0]
        self._init_sagemaker_session_if_does_not_exist(instance_type)

        if image_uri:
            self.image_uri = image_uri
        if not self.image_uri:
            self.image_uri = self.serving_image_uri(
                region_name=self.sagemaker_session.boto_session.region_name,
                instance_type=instance_type,
            )
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