diff --git a/invokeai/backend/flux/controlnet/xlabs_controlnet_flux.py b/invokeai/backend/flux/controlnet/xlabs_controlnet_flux.py
index 0e99fac4a1..b5f24bc554 100644
--- a/invokeai/backend/flux/controlnet/xlabs_controlnet_flux.py
+++ b/invokeai/backend/flux/controlnet/xlabs_controlnet_flux.py
@@ -5,17 +5,11 @@
 import torch
 from einops import rearrange
 
+from invokeai.backend.flux.controlnet.zero_module import zero_module
 from invokeai.backend.flux.model import FluxParams
 from invokeai.backend.flux.modules.layers import DoubleStreamBlock, EmbedND, MLPEmbedder, timestep_embedding
 
 
-def _zero_module(module: torch.nn.Module) -> torch.nn.Module:
-    """Initialize the parameters of a module to zero."""
-    for p in module.parameters():
-        torch.nn.init.zeros_(p)
-    return module
-
-
 class XLabsControlNetFlux(torch.nn.Module):
     """A ControlNet model for FLUX.
 
@@ -63,7 +57,7 @@ class XLabsControlNetFlux(torch.nn.Module):
         self.controlnet_blocks = torch.nn.ModuleList([])
         for _ in range(controlnet_depth):
             controlnet_block = torch.nn.Linear(self.hidden_size, self.hidden_size)
-            controlnet_block = _zero_module(controlnet_block)
+            controlnet_block = zero_module(controlnet_block)
             self.controlnet_blocks.append(controlnet_block)
         self.pos_embed_input = torch.nn.Linear(self.in_channels, self.hidden_size, bias=True)
         self.input_hint_block = torch.nn.Sequential(
@@ -81,7 +75,7 @@ class XLabsControlNetFlux(torch.nn.Module):
             torch.nn.SiLU(),
             torch.nn.Conv2d(16, 16, 3, padding=1, stride=2),
             torch.nn.SiLU(),
-            _zero_module(torch.nn.Conv2d(16, 16, 3, padding=1)),
+            zero_module(torch.nn.Conv2d(16, 16, 3, padding=1)),
         )
 
     def forward(
diff --git a/invokeai/backend/flux/controlnet/zero_module.py b/invokeai/backend/flux/controlnet/zero_module.py
new file mode 100644
index 0000000000..53a21861a9
--- /dev/null
+++ b/invokeai/backend/flux/controlnet/zero_module.py
@@ -0,0 +1,12 @@
+from typing import TypeVar
+
+import torch
+
+T = TypeVar("T", bound=torch.nn.Module)
+
+
+def zero_module(module: T) -> T:
+    """Initialize the parameters of a module to zero."""
+    for p in module.parameters():
+        torch.nn.init.zeros_(p)
+    return module