Update app.py

app.py

@@ -47,7 +47,7 @@ from torchvision import transforms
 controlnet = ControlNetModel.from_pretrained(
     "briaai/BRIA-2.2-ControlNet-Canny",
     torch_dtype=torch.float16
-).to('cuda')
+) #.to('cuda')
 
 pipe = StableDiffusionXLControlNetPipeline.from_pretrained(
     "briaai/BRIA-2.2",
@@ -56,7 +56,7 @@ pipe = StableDiffusionXLControlNetPipeline.from_pretrained(
     device_map='auto',
     low_cpu_mem_usage=True,
     offload_state_dict=True,
-).to('cuda')
+) #.to('cuda')
 pipe.scheduler = EulerAncestralDiscreteScheduler(
     beta_start=0.00085,
     beta_end=0.012,
@@ -105,6 +105,7 @@ def process(input_image, prompt, negative_prompt, num_steps, controlnet_conditio
 
 @spaces.GPU
 def generate_(prompt, negative_prompt, canny_image, num_steps, controlnet_conditioning_scale, seed):
+    pipe.to('cuda')
     generator = torch.manual_seed(seed)
     images = pipe(
     prompt, negative_prompt=negative_prompt, image=canny_image, num_inference_steps=num_steps, controlnet_conditioning_scale=float(controlnet_conditioning_scale),