src/sagemaker/serve/builder/tei_builder.py [172:210]:
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            return predictor

        if "mode" in kwargs:
            del kwargs["mode"]
        if "role" in kwargs:
            self.pysdk_model.role = kwargs.get("role")
            del kwargs["role"]

        if not _is_optimized(self.pysdk_model):
            env_vars = {}
            if str(Mode.LOCAL_CONTAINER) in self.modes:
                # upload model artifacts to S3 if LOCAL_CONTAINER -> SAGEMAKER_ENDPOINT
                self.pysdk_model.model_data, env_vars = self._prepare_for_mode(
                    model_path=self.model_path, should_upload_artifacts=True
                )
            else:
                _, env_vars = self._prepare_for_mode()

            self.env_vars.update(env_vars)
            self.pysdk_model.env.update(self.env_vars)

        # if the weights have been cached via local container mode -> set to offline
        if str(Mode.LOCAL_CONTAINER) in self.modes:
            self.pysdk_model.env.update({"HF_HUB_OFFLINE": "1"})
        else:
            # if has not been built for local container we must use cache
            # that hosting has write access to.
            self.pysdk_model.env["HF_HOME"] = "/tmp"
            self.pysdk_model.env["HUGGINGFACE_HUB_CACHE"] = "/tmp"

        if "endpoint_logging" not in kwargs:
            kwargs["endpoint_logging"] = True

        if self.nb_instance_type and "instance_type" not in kwargs:
            kwargs.update({"instance_type": self.nb_instance_type})
        elif not self.nb_instance_type and "instance_type" not in kwargs:
            raise ValueError(
                "Instance type must be provided when deploying " "to SageMaker Endpoint mode."
            )
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src/sagemaker/serve/builder/tgi_builder.py [211:249]:
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            return predictor

        if "mode" in kwargs:
            del kwargs["mode"]
        if "role" in kwargs:
            self.pysdk_model.role = kwargs.get("role")
            del kwargs["role"]

        if not _is_optimized(self.pysdk_model):
            env_vars = {}
            if str(Mode.LOCAL_CONTAINER) in self.modes:
                # upload model artifacts to S3 if LOCAL_CONTAINER -> SAGEMAKER_ENDPOINT
                self.pysdk_model.model_data, env_vars = self._prepare_for_mode(
                    model_path=self.model_path, should_upload_artifacts=True
                )
            else:
                _, env_vars = self._prepare_for_mode()

            self.env_vars.update(env_vars)
            self.pysdk_model.env.update(self.env_vars)

        # if the weights have been cached via local container mode -> set to offline
        if str(Mode.LOCAL_CONTAINER) in self.modes:
            self.pysdk_model.env.update({"HF_HUB_OFFLINE": "1"})
        else:
            # if has not been built for local container we must use cache
            # that hosting has write access to.
            self.pysdk_model.env["HF_HOME"] = "/tmp"
            self.pysdk_model.env["HUGGINGFACE_HUB_CACHE"] = "/tmp"

        if "endpoint_logging" not in kwargs:
            kwargs["endpoint_logging"] = True

        if self.nb_instance_type and "instance_type" not in kwargs:
            kwargs.update({"instance_type": self.nb_instance_type})
        elif not self.nb_instance_type and "instance_type" not in kwargs:
            raise ValueError(
                "Instance type must be provided when deploying " "to SageMaker Endpoint mode."
            )
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