Update app.py

app.py

@@ -11,12 +11,12 @@ if torch.cuda.is_available():
     pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
     pipe.enable_xformers_memory_efficient_attention()
     pipe = pipe.to(device)
-    pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
+    #pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
     torch.cuda.empty_cache()
-    refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", use_safetensors=True, torch_dtype=torch.float16, variant="fp16")
-    refiner.enable_xformers_memory_efficient_attention()
-    refiner.enable_sequential_cpu_offload()
-    refiner.unet = torch.compile(refiner.unet, mode="reduce-overhead", fullgraph=True)
+    #refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", use_safetensors=True, torch_dtype=torch.float16, variant="fp16")
+    #refiner.enable_xformers_memory_efficient_attention()
+    #refiner.enable_sequential_cpu_offload()
+    #refiner.unet = torch.compile(refiner.unet, mode="reduce-overhead", fullgraph=True)
 else: 
     pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True)
     pipe = pipe.to(device)