Initialize framework and framework version in post_init

sagemaker-serve/src/sagemaker/serve/model_builder.py

@@ -489,6 +489,11 @@ def _initialize_defaults(self) -> None:
         self.container_config = "host"
         self.inference_recommender_job_results = None
         self.container_log_level = logging.INFO
+
+        if not hasattr(self, 'framework') or self.framework is None:
+            self.framework = None
+        if not hasattr(self, 'framework_version') or self.framework_version is None:
+            self.framework_version = None
 
     def _fetch_default_instance_type_for_custom_model(self) -> str:
         hosting_configs = self._fetch_hosting_configs_for_custom_model()

v3-examples/ml-ops-examples/v3-model-registry-example/v3-model-registry-example.ipynb

@@ -185,18 +185,24 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from sagemaker.core.resources import ModelPackage\n",
+    "from sagemaker.serve.model_builder import ModelBuilder\n",
+    "\n",
+    "# Get the registered ModelPackage using the ARN as model_package_name\n",
+    "model_package = ModelPackage.get(model_package_name=registered_model_package_arn)\n",
+    "\n",
+    "s3_model_data_uri = model_package.inference_specification.containers[0].model_data_url\n",
+    "image_uri = model_package.inference_specification.containers[0].image\n",
     "\n",
-    "# Use the model_package in section above\n",
     "model_builder = ModelBuilder(\n",
-    "    model_package_arn=registered_model_package_arn,\n",
+    "    s3_model_data_url=s3_model_data_uri,\n",
+    "    image_uri=image_uri,\n",
     "    role_arn=role,\n",
     "    sagemaker_session=sagemaker_session\n",
     ")\n",
     "\n",
-    "\n",
-    "\n",
     "# Build the model\n",
-    "model = model_builder.build(model_name=\"my-model-from-registry\")"
+    "model = model_builder.build(model_name=\"my-model-from-registry\")\n"
    ]
   }
  ],