diff --git a/test/test_utils.py b/test/test_utils.py
index 47669952..39c7daf6 100644
--- a/test/test_utils.py
+++ b/test/test_utils.py
@@ -1,7 +1,7 @@
 # Copyright (c) 2021, Zhiqiang Wang. All Rights Reserved.
-import pytest
-
+from pathlib import Path
 import numpy as np
+import torch
 from torch import nn, Tensor
 
 from yolort.utils import (
@@ -11,14 +11,18 @@
 )
 
 
-@pytest.mark.skip("Temporarily close the test here.")
 def test_update_module_state_from_ultralytics():
+    yolov5s_r40_path = Path('yolov5s.pt')
+
+    if not yolov5s_r40_path.is_file():
+        yolov5s_r40_url = 'https://github.com/ultralytics/yolov5/releases/download/v4.0/yolov5s.pt'
+        torch.hub.download_url_to_file(yolov5s_r40_url, yolov5s_r40_path, hash_prefix='9ca9a642')
+
     model = update_module_state_from_ultralytics(
+        str(yolov5s_r40_path),
         arch='yolov5s',
-        version='v4.0',
         feature_fusion_type='PAN',
         num_classes=80,
-        custom_path_or_model=None,
     )
     assert isinstance(model, nn.Module)
 
@@ -33,7 +37,7 @@ def test_read_image_to_tensor():
 
 
 def test_get_image_from_url():
-    url = "https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg"
+    url = 'https://raw.githubusercontent.com/zhiqwang/yolov5-rt-stack/master/test/assets/zidane.jpg'
     img = get_image_from_url(url)
     assert isinstance(img, np.ndarray)
     assert tuple(img.shape) == (720, 1280, 3)
diff --git a/yolort/utils/update_module_state.py b/yolort/utils/update_module_state.py
index 68d648b0..ffddc774 100644
--- a/yolort/utils/update_module_state.py
+++ b/yolort/utils/update_module_state.py
@@ -1,8 +1,7 @@
 # Copyright (c) 2020, Zhiqiang Wang. All Rights Reserved.
-from typing import Any, Optional
+from typing import Any
 
 from functools import reduce
-import torch
 from torch import nn
 
 from yolort.models import yolo
@@ -17,12 +16,12 @@
 
 
 def update_module_state_from_ultralytics(
-    custom_path_path: str,
-    path_to_yolov5: Optional[str] = None,
+    model_path: str,
     arch: str = 'yolov5s',
     feature_fusion_type: str = 'PAN',
     num_classes: int = 80,
     set_fp16: bool = True,
+    verbose: bool = False,
     **kwargs: Any,
 ):
     """
@@ -31,9 +30,7 @@ def update_module_state_from_ultralytics(
     wish to re-train.
 
     Args:
-        custom_path_path (str): Path to your custom model.
-        path_to_yolov5 (Optional[str]): Path of the local yolov5 repo.
-            Default: None.
+        model_path (str): Path to your custom model.
         arch (str): yolo architecture. Possible values are 'yolov5s', 'yolov5m' and 'yolov5l'.
             Default: 'yolov5s'.
         feature_fusion_type (str): the type of fature fusion. Possible values are PAN and TAN.
@@ -42,12 +39,11 @@ def update_module_state_from_ultralytics(
             Default: 80.
         set_fp16 (bool): allow selective conversion to fp16 or not.
             Default: True.
+        verbose (bool): print all information to screen. Default: True.
     """
 
-    if path_to_yolov5 is not None:
-        model = torch.hub.load(path_to_yolov5, 'custom', path=custom_path_path, source='local')
-    else:
-        model = torch.hub.load('ultralytics/yolov5', 'custom', path=custom_path_path)
+    from yolort.v5 import load_model
+    model = load_model(model_path, autoshape=False, verbose=verbose)
 
     key_arch = f'{arch}_{feature_fusion_type.lower()}_v4.0'
     if key_arch not in ARCHITECTURE_MAPS: