Update app.py

app.py

@@ -18,7 +18,7 @@ pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
 pipe = pipe.to(device)
 
 MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 1024
+MAX_IMAGE_SIZE = 512
 
 def calculate_duration(width, height, num_inference_steps):
     # Примерная оценка времени выполнения
@@ -140,67 +140,7 @@ with gr.Blocks(theme=CustomTheme(), css=css) as demo:
 
         result = gr.Image(label="Result", show_label=False)
 
-        with gr.Accordion("Advanced Settings", open=False):
-            negative_prompt = gr.Text(
-                label="Negative Prompt",
-                max_lines=1,
-                placeholder="Enter a negative prompt",
-                visible=False,
-            )
-
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=MAX_SEED,
-                step=1,
-                value=0,
-            )
-
-            randomize_seed = gr.Checkbox(label="Randomize Seed", value=True)
-
-            with gr.Row():
-                width = gr.Slider(
-                    label="Width",
-                    minimum=512,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024, 
-                )
-
-                height = gr.Slider(
-                    label="Height",
-                    minimum=512,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,
-                )
-
-            with gr.Row():
-                guidance_scale = gr.Slider(
-                    label="Guidance Scale",
-                    minimum=0.0,
-                    maximum=7.5,
-                    step=0.1,
-                    value=4.5,
-                )
-
-                num_inference_steps = gr.Slider(
-                    label="Number of Inference Steps",
-                    minimum=1,
-                    maximum=50,
-                    step=1,
-                    value=40, 
-                )
-
-        gr.Examples(
-            examples=examples,
-            inputs=[prompt],
-            outputs=[result, seed],
-            fn=infer,
-            cache_examples=True,
-            cache_mode="lazy"
-        )
-
+       
     # Use click method for the button and submit for the text field
     run_button.click(
         fn=infer,