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
 
 
 # @spaces.GPU #[uncomment to use ZeroGPU]
@@ -102,35 +102,18 @@ with gr.Blocks(css=css) as demo:
             with gr.Row():
                 width = gr.Slider(
                     label="Width",
-                    minimum=256,
+                    minimum=512,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024,  # Replace with defaults that work for your model
+                    value=512,  # Replace with defaults that work for your model
                 )
 
                 height = gr.Slider(
                     label="Height",
-                    minimum=256,
+                    minimum=512,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024,  # Replace with defaults that work for your model
-                )
-
-            with gr.Row():
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.0,
-                    maximum=10.0,
-                    step=0.1,
-                    value=0.0,  # Replace with defaults that work for your model
-                )
-
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=50,
-                    step=1,
-                    value=2,  # Replace with defaults that work for your model
+                    value=512,  # Replace with defaults that work for your model
                 )
 
         gr.Examples(examples=examples, inputs=[prompt])