diff --git a/examples/instance_kind/model.py b/examples/instance_kind/model.py
index baff8e7b..0a944136 100644
--- a/examples/instance_kind/model.py
+++ b/examples/instance_kind/model.py
@@ -1,4 +1,4 @@
-# Copyright 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# Copyright 2023-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 #
 # Redistribution and use in source and binary forms, with or without
 # modification, are permitted provided that the following conditions
@@ -24,8 +24,8 @@
 # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-import numpy as np
 import torch
+from torchvision import models
 import triton_python_backend_utils as pb_utils
 from torch.utils.dlpack import to_dlpack
 
@@ -49,21 +49,7 @@ def initialize(self, args):
         device = "cuda" if args["model_instance_kind"] == "GPU" else "cpu"
         device_id = args["model_instance_device_id"]
         self.device = f"{device}:{device_id}"
-        # This example is configured to work with torch=1.13
-        # and torchvision=0.14. Thus, we need to provide a proper tag `0.14.1`
-        # to make sure loaded Resnet50 is compatible with
-        # installed `torchvision`.
-        # Refer to README for installation instructions.
-        self.model = (
-            torch.hub.load(
-                "pytorch/vision:v0.14.1",
-                "resnet50",
-                weights="IMAGENET1K_V2",
-                skip_validation=True,
-            )
-            .to(self.device)
-            .eval()
-        )
+        self.model = models.resnet50(weights=models.ResNet50_Weights.IMAGENET1K_V2).to(self.device).eval()
 
     def execute(self, requests):
         """