diff --git a/examples/community/pipeline_stable_diffusion_xl_controlnet_adapter_inpaint.py b/examples/community/pipeline_stable_diffusion_xl_controlnet_adapter_inpaint.py
index bc612edbc20e..ca2a1521d3d5 100644
--- a/examples/community/pipeline_stable_diffusion_xl_controlnet_adapter_inpaint.py
+++ b/examples/community/pipeline_stable_diffusion_xl_controlnet_adapter_inpaint.py
@@ -1470,7 +1470,15 @@ def __call__(
         height, width = self._default_height_width(height, width, adapter_image)
         device = self._execution_device
 
-        adapter_input = _preprocess_adapter_image(adapter_image, height, width).to(device)
+        if isinstance(adapter, MultiAdapter):
+            adapter_input = []
+            for one_image in adapter_image:
+                one_image = _preprocess_adapter_image(one_image, height, width)
+                one_image = one_image.to(device=device, dtype=adapter.dtype)
+                adapter_input.append(one_image)
+        else:
+            adapter_input = _preprocess_adapter_image(adapter_image, height, width)
+            adapter_input = adapter_input.to(device=device, dtype=adapter.dtype)
 
         original_size = original_size or (height, width)
         target_size = target_size or (height, width)
@@ -1643,10 +1651,14 @@ def denoising_value_valid(dnv):
         extra_step_kwargs = self.prepare_extra_step_kwargs(generator, eta)
 
         # 10. Prepare added time ids & embeddings & adapter features
-        adapter_input = adapter_input.type(latents.dtype)
-        adapter_state = adapter(adapter_input)
-        for k, v in enumerate(adapter_state):
-            adapter_state[k] = v * adapter_conditioning_scale
+        if isinstance(adapter, MultiAdapter):
+            adapter_state = adapter(adapter_input, adapter_conditioning_scale)
+            for k, v in enumerate(adapter_state):
+                adapter_state[k] = v
+        else:
+            adapter_state = adapter(adapter_input)
+            for k, v in enumerate(adapter_state):
+                adapter_state[k] = v * adapter_conditioning_scale
         if num_images_per_prompt > 1:
             for k, v in enumerate(adapter_state):
                 adapter_state[k] = v.repeat(num_images_per_prompt, 1, 1, 1)