Update app.py

app.py

@@ -7,7 +7,6 @@ import torch
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 if torch.cuda.is_available():
-    torch.cuda.max_memory_allocated(device=device)
     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)
@@ -16,7 +15,7 @@ else:
     pipe = pipe.to(device)
 
 MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 1024
+MAX_IMAGE_SIZE = 512  # 이미지 크기를 512로 설정
 
 def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
     if randomize_seed:
@@ -72,7 +71,7 @@ with gr.Blocks(css=css) as demo:
                 label="Prompt / 프롬프트",
                 show_label=False,
                 max_lines=1,
-                placeholder="Enter your prompt / 프롬프트를 입력하세요 (영어가 더욱 정확합니다.)",
+                placeholder="Enter your prompt / 프롬프트를 입력하세요",
                 container=False,
             )
             
@@ -106,7 +105,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024,
+                    value=512,
                 )
                 
                 height = gr.Slider(
@@ -114,7 +113,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024,
+                    value=512,
                 )
             
             with gr.Row():
@@ -132,7 +131,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=1,
                     maximum=50,
                     step=1,
-                    value=25,
+                    value=20,  # 추론 단계를 20으로 설정하여 시간 단축
                 )
         
         gr.Examples(