diff --git a/modules/nsf_hifigan/models.py b/modules/nsf_hifigan/models.py
index a77eb0a3..59300ebb 100644
--- a/modules/nsf_hifigan/models.py
+++ b/modules/nsf_hifigan/models.py
@@ -7,13 +7,19 @@
 import torch.nn.functional as F
 from lightning.pytorch.utilities.rank_zero import rank_zero_info
 from torch.nn import Conv1d, ConvTranspose1d
-from torch.nn.utils import weight_norm, remove_weight_norm
+# from torch.nn.utils import weight_norm, remove_weight_norm
 
 from .env import AttrDict
 from .utils import init_weights, get_padding
 
 LRELU_SLOPE = 0.1
-
+_OLD_WEIGHT_NORM = False
+try:
+    from torch.nn.utils.parametrizations import weight_norm
+except ImportError:
+    from torch.nn.utils import weight_norm
+    from torch.nn.utils import remove_weight_norm
+    _OLD_WEIGHT_NORM = True
 
 def load_model(model_path: pathlib.Path):
     config_file = model_path.with_name('config.json')
@@ -67,10 +73,17 @@ def forward(self, x):
         return x
 
     def remove_weight_norm(self):
-        for l in self.convs1:
-            remove_weight_norm(l)
-        for l in self.convs2:
-            remove_weight_norm(l)
+            global _OLD_WEIGHT_NORM
+            if _OLD_WEIGHT_NORM:
+                for l in self.convs1:
+                    remove_weight_norm(l)
+                for l in self.convs2:
+                    remove_weight_norm(l)
+            else:
+                for l in self.convs1:
+                    torch.nn.utils.parametrize.remove_parametrizations(l)
+                for l in self.convs2:
+                    torch.nn.utils.parametrize.remove_parametrizations(l)
 
 
 class ResBlock2(torch.nn.Module):
@@ -93,8 +106,15 @@ def forward(self, x):
         return x
 
     def remove_weight_norm(self):
-        for l in self.convs:
-            remove_weight_norm(l)
+    
+        global _OLD_WEIGHT_NORM
+        if _OLD_WEIGHT_NORM:
+            for l in self.convs:
+                remove_weight_norm(l)
+    
+        else:
+            for l in self.convs:
+                torch.nn.utils.parametrize.remove_parametrizations(l)
 
 
 class SineGen(torch.nn.Module):
@@ -285,10 +305,22 @@ def forward(self, x, f0):
         return x
 
     def remove_weight_norm(self):
-        rank_zero_info('Removing weight norm...')
-        for l in self.ups:
-            remove_weight_norm(l)
-        for l in self.resblocks:
-            l.remove_weight_norm()
-        remove_weight_norm(self.conv_pre)
-        remove_weight_norm(self.conv_post)
+        # rank_zero_info('Removing weight norm...')
+        print('Removing weight norm...')
+        global _OLD_WEIGHT_NORM
+        if _OLD_WEIGHT_NORM:
+            for l in self.ups:
+                remove_weight_norm(l)
+            for l in self.resblocks:
+                l.remove_weight_norm()
+
+            remove_weight_norm(self.conv_pre)
+            remove_weight_norm(self.conv_post)
+        else:
+            for l in self.ups:
+                torch.nn.utils.parametrize.remove_parametrizations(l)
+            for l in self.resblocks:
+                l.remove_weight_norm()
+
+            torch.nn.utils.parametrize.remove_parametrizations(self.conv_pre)
+            torch.nn.utils.parametrize.remove_parametrizations(self.conv_post)