diff --git a/invokeai/backend/model_manager/load/model_cache/torch_module_autocast/custom_modules/custom_embedding.py b/invokeai/backend/model_manager/load/model_cache/torch_module_autocast/custom_modules/custom_embedding.py
index e6f0c5df21..e622b678fa 100644
--- a/invokeai/backend/model_manager/load/model_cache/torch_module_autocast/custom_modules/custom_embedding.py
+++ b/invokeai/backend/model_manager/load/model_cache/torch_module_autocast/custom_modules/custom_embedding.py
@@ -20,6 +20,9 @@ class CustomEmbedding(torch.nn.Embedding, CustomModuleMixin):
         )
 
     def forward(self, input: torch.Tensor) -> torch.Tensor:
+        if len(self._patches_and_weights) > 0:
+            raise RuntimeError("Embedding layers do not support patches")
+
         if self._device_autocasting_enabled:
             return self._autocast_forward(input)
         else:
diff --git a/invokeai/backend/model_manager/load/model_cache/torch_module_autocast/custom_modules/custom_group_norm.py b/invokeai/backend/model_manager/load/model_cache/torch_module_autocast/custom_modules/custom_group_norm.py
index 66a46ac7ea..d02e2d533f 100644
--- a/invokeai/backend/model_manager/load/model_cache/torch_module_autocast/custom_modules/custom_group_norm.py
+++ b/invokeai/backend/model_manager/load/model_cache/torch_module_autocast/custom_modules/custom_group_norm.py
@@ -13,6 +13,9 @@ class CustomGroupNorm(torch.nn.GroupNorm, CustomModuleMixin):
         return torch.nn.functional.group_norm(input, self.num_groups, weight, bias, self.eps)
 
     def forward(self, input: torch.Tensor) -> torch.Tensor:
+        if len(self._patches_and_weights) > 0:
+            raise RuntimeError("GroupNorm layers do not support patches")
+
         if self._device_autocasting_enabled:
             return self._autocast_forward(input)
         else: