diff --git a/backends/arm/test/models/test_mobilenet_v2_arm.py b/backends/arm/test/models/test_mobilenet_v2_arm.py
index ee136d1b480..6c247ac10e9 100644
--- a/backends/arm/test/models/test_mobilenet_v2_arm.py
+++ b/backends/arm/test/models/test_mobilenet_v2_arm.py
@@ -9,11 +9,11 @@
 import unittest
 
 import torch
-import torchvision.models as models
 from executorch.backends.arm.test import common
 
 from executorch.backends.arm.test.tester.arm_tester import ArmTester
 from executorch.backends.xnnpack.test.tester.tester import Quantize
+from torchvision import models
 from torchvision.models.mobilenetv2 import MobileNet_V2_Weights
 
 
diff --git a/backends/xnnpack/test/models/inception_v3.py b/backends/xnnpack/test/models/inception_v3.py
index b861afc5cd5..ddadbdd2f81 100644
--- a/backends/xnnpack/test/models/inception_v3.py
+++ b/backends/xnnpack/test/models/inception_v3.py
@@ -7,9 +7,9 @@
 import unittest
 
 import torch
-import torchvision.models as models
 from executorch.backends.xnnpack.test.tester import Tester
 from executorch.backends.xnnpack.test.tester.tester import Quantize
+from torchvision import models
 
 
 class TestInceptionV3(unittest.TestCase):
diff --git a/backends/xnnpack/test/models/mobilenet_v2.py b/backends/xnnpack/test/models/mobilenet_v2.py
index 53bcedd0a90..c2bc364b9c4 100644
--- a/backends/xnnpack/test/models/mobilenet_v2.py
+++ b/backends/xnnpack/test/models/mobilenet_v2.py
@@ -7,9 +7,9 @@
 import unittest
 
 import torch
-import torchvision.models as models
 from executorch.backends.xnnpack.test.tester import Tester
 from executorch.backends.xnnpack.test.tester.tester import Quantize
+from torchvision import models
 from torchvision.models.mobilenetv2 import MobileNet_V2_Weights
 
 
diff --git a/backends/xnnpack/test/models/mobilenet_v3.py b/backends/xnnpack/test/models/mobilenet_v3.py
index 3da2e3bf42c..d990fa0e3bf 100644
--- a/backends/xnnpack/test/models/mobilenet_v3.py
+++ b/backends/xnnpack/test/models/mobilenet_v3.py
@@ -7,9 +7,9 @@
 import unittest
 
 import torch
-import torchvision.models as models
 from executorch.backends.xnnpack.test.tester import Tester
 from executorch.backends.xnnpack.test.tester.tester import Quantize
+from torchvision import models
 
 
 class TestMobileNetV3(unittest.TestCase):
diff --git a/backends/xnnpack/test/models/torchvision_vit.py b/backends/xnnpack/test/models/torchvision_vit.py
index e4b387e0f79..836a9056857 100644
--- a/backends/xnnpack/test/models/torchvision_vit.py
+++ b/backends/xnnpack/test/models/torchvision_vit.py
@@ -7,8 +7,8 @@
 import unittest
 
 import torch
-import torchvision.models as models
 from executorch.backends.xnnpack.test.tester import Tester
+from torchvision import models
 
 
 class TestViT(unittest.TestCase):
diff --git a/examples/qualcomm/oss_scripts/ssd300_vgg16.py b/examples/qualcomm/oss_scripts/ssd300_vgg16.py
index 6457b68f7d6..936db49d0a1 100644
--- a/examples/qualcomm/oss_scripts/ssd300_vgg16.py
+++ b/examples/qualcomm/oss_scripts/ssd300_vgg16.py
@@ -109,7 +109,11 @@ def SSD300VGG16(pretrained_weight_model):
     from model import SSD300
 
     model = SSD300(n_classes=21)
-    checkpoint = torch.load(pretrained_weight_model, map_location="cpu")
+    # TODO: If possible, it's better to set weights_only to True
+    # https://pytorch.org/docs/stable/generated/torch.load.html
+    checkpoint = torch.load(
+        pretrained_weight_model, map_location="cpu", weights_only=False
+    )
     model.load_state_dict(checkpoint["model"].state_dict())
 
     return model.eval()
diff --git a/examples/qualcomm/scripts/mobilebert_fine_tune.py b/examples/qualcomm/scripts/mobilebert_fine_tune.py
index 84d130d4244..cb067690f94 100755
--- a/examples/qualcomm/scripts/mobilebert_fine_tune.py
+++ b/examples/qualcomm/scripts/mobilebert_fine_tune.py
@@ -204,6 +204,8 @@ def get_fine_tuned_mobilebert(artifacts_dir, pretrained_weight, batch_size):
             )
 
     model.load_state_dict(
+        # TODO: If possible, it's better to set weights_only to True
+        # https://pytorch.org/docs/stable/generated/torch.load.html
         torch.load(
             (
                 f"{artifacts_dir}/finetuned_mobilebert_epoch_{epochs}.model"
@@ -211,6 +213,7 @@ def get_fine_tuned_mobilebert(artifacts_dir, pretrained_weight, batch_size):
                 else pretrained_weight
             ),
             map_location=torch.device("cpu"),
+            weights_only=False,
         ),
     )
 
diff --git a/exir/serde/export_serialize.py b/exir/serde/export_serialize.py
index fef2b2411fa..87691dfbee2 100644
--- a/exir/serde/export_serialize.py
+++ b/exir/serde/export_serialize.py
@@ -242,7 +242,9 @@ def deserialize_torch_artifact(serialized: bytes):
         return {}
     buffer = io.BytesIO(serialized)
     buffer.seek(0)
-    return torch.load(buffer)
+    # TODO: If possible, it's better to set weights_only to True
+    # https://pytorch.org/docs/stable/generated/torch.load.html
+    return torch.load(buffer, weights_only=False)
 
 
 def _sympy_int_to_int(val: sympy.Expr):
diff --git a/requirements-lintrunner.txt b/requirements-lintrunner.txt
index c72ec10f35e..da10dd53cab 100644
--- a/requirements-lintrunner.txt
+++ b/requirements-lintrunner.txt
@@ -10,7 +10,7 @@ flake8-comprehensions==3.12.0
 flake8-pyi==23.5.0
 mccabe==0.7.0
 pycodestyle==2.10.0
-torchfix==0.1.1
+torchfix==0.5.0
 
 # UFMT
 black==24.2.0