Update device info

app.py

@@ -63,7 +63,7 @@ pipeline = DiffusionPipeline.from_pretrained(
     variant="fp16",
     use_safetensors=True,
     torch_dtype=dtype,
-).to(device)
+).to('cuda')
 
 if is_attention_slicing_enabled:
     pipeline.enable_attention_slicing()
@@ -80,8 +80,8 @@ def remove(gradio_image, rm_guidance_scale=9, num_inference_steps=50, seed=42, s
 
         source_image_pure = gradio_image["background"]
         mask_image_pure = gradio_image["layers"][0]
-        source_image = preprocess_image(source_image_pure.convert('RGB'), device)
-        mask = preprocess_mask(mask_image_pure, device)
+        source_image = preprocess_image(source_image_pure.convert('RGB'), 'cuda')
+        mask = preprocess_mask(mask_image_pure, 'cuda')
         
         START_STEP = 0 # AAS start step
         END_STEP = int(strength * num_inference_steps) # AAS end step