Try use SDXL with other controlnet

app.py

@@ -5,8 +5,9 @@ import numpy as np
 
 # import spaces #[uncomment to use ZeroGPU]
 from diffusers import (
-    StableDiffusionControlNetImg2ImgPipeline,
+    # StableDiffusionControlNetImg2ImgPipeline,
     ControlNetModel,
+    StableDiffusionXLControlNetPipeline,
 )
 import torch
 
@@ -24,17 +25,28 @@ if torch.cuda.is_available():
 else:
     torch_dtype = torch.float32
 
+# controlnet = ControlNetModel.from_pretrained(
+#     "lllyasviel/sd-controlnet-canny", torch_dtype=torch.float32
+# )
+
 controlnet = ControlNetModel.from_pretrained(
-    "lllyasviel/sd-controlnet-canny", torch_dtype=torch.float32
+    "diffusers/controlnet-canny-sdxl-1.0", torch_dtype=torch.float16
 )
 
 # pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
-pipe = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
-    model_repo_id,
+# pipe = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
+#     model_repo_id,
+#     controlnet=controlnet,
+#     torch_dtype=torch_dtype,
+# ).to(device)
+pipe = StableDiffusionXLControlNetPipeline.from_pretrained(
+    "stabilityai/stable-diffusion-xl-base-1.0",
     controlnet=controlnet,
-    torch_dtype=torch_dtype,
+    torch_dtype=torch.float16,
+    variant="fp16",
+    use_safetensors=True,
 ).to(device)
-pipe = pipe.to(device)
+# pipe = pipe.to(device)
 canny = CannyDetector()
 
 MAX_SEED = np.iinfo(np.int32).max