diff --git a/notebooks/community/model_garden/model_garden_pytorch_owlvit.ipynb b/notebooks/community/model_garden/model_garden_pytorch_owlvit.ipynb
index da8484b6a..69a1aabe3 100644
--- a/notebooks/community/model_garden/model_garden_pytorch_owlvit.ipynb
+++ b/notebooks/community/model_garden/model_garden_pytorch_owlvit.ipynb
@@ -149,6 +149,9 @@
         "\n",
         "models, endpoints = {}, {}\n",
         "\n",
+        "# @markdown Set use_dedicated_endpoint to False if you don't want to use [dedicated endpoint](https://cloud.google.com/vertex-ai/docs/general/deployment#create-dedicated-endpoint). Note that [dedicated endpoint does not support VPC Service Controls](https://cloud.google.com/vertex-ai/docs/predictions/choose-endpoint-type), uncheck the box if you are using VPC-SC.\n",
+        "use_dedicated_endpoint = True  # @param {type:\"boolean\"}\n",
+        "\n",
         "# @markdown Click \"Show Code\" to see more details."
       ]
     },
@@ -185,9 +188,19 @@
         "ACCELERATOR_COUNT = 1\n",
         "\n",
         "\n",
-        "def deploy_model(model_id, task, accelerator_type, machine_type, accelerator_count):\n",
+        "def deploy_model(\n",
+        "    model_id: str,\n",
+        "    task: str,\n",
+        "    machine_type: str = \"n1-standard-8\",\n",
+        "    accelerator_type: str = \"NVIDIA_TESLA_T4\",\n",
+        "    accelerator_count: int = 1,\n",
+        "    use_dedicated_endpoint: bool = False,\n",
+        "):\n",
         "    model_name = \"owl-vit\"\n",
-        "    endpoint = aiplatform.Endpoint.create(display_name=f\"{model_name}-endpoint\")\n",
+        "    endpoint = aiplatform.Endpoint.create(\n",
+        "        display_name=f\"{model_name}-endpoint\",\n",
+        "        dedicated_endpoint_enabled=use_dedicated_endpoint,\n",
+        "    )\n",
         "    serving_env = {\n",
         "        \"MODEL_ID\": model_id,\n",
         "        \"TASK\": task,\n",
@@ -225,14 +238,19 @@
         ")\n",
         "\n",
         "\n",
-        "models[\"model\"], endpoints[\"endpoint\"] = deploy_model(\n",
+        "LABEL = \"owl-vit\"\n",
+        "models[LABEL], endpoints[LABEL] = deploy_model(\n",
         "    model_id=\"google/owlvit-base-patch32\",\n",
         "    task=\"zero-shot-object-detection\",\n",
-        "    accelerator_type=ACCELERATOR_TYPE,\n",
         "    machine_type=MACHINE_TYPE,\n",
+        "    accelerator_type=ACCELERATOR_TYPE,\n",
         "    accelerator_count=ACCELERATOR_COUNT,\n",
+        "    use_dedicated_endpoint=use_dedicated_endpoint,\n",
         ")\n",
         "\n",
+        "endpoint = endpoints[LABEL]\n",
+        "model = models[LABEL]\n",
+        "\n",
         "# @markdown Click \"Show Code\" to see more details."
       ]
     },
@@ -266,7 +284,9 @@
         "instances = [\n",
         "    {\"image\": common_util.image_to_base64(image), \"text\": text},\n",
         "]\n",
-        "preds = endpoints[\"endpoint\"].predict(instances=instances).predictions\n",
+        "preds = endpoint.predict(\n",
+        "    instances=instances, use_dedicated_endpoint=use_dedicated_endpoint\n",
+        ").predictions\n",
         "\n",
         "\n",
         "def draw_image_with_boxes(image, boxes):\n",