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 = 520
+MAX_IMAGE_SIZE = 750
 
 from datasets import load_dataset, Dataset
 
@@ -91,7 +91,7 @@ css = """
 
 with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
-        gr.Markdown(" # Text-to-Image Gradio Template")
+        gr.Markdown(" # Text-to-Image Wom_Test")
 
         with gr.Row():
             prompt = gr.Text(
@@ -127,25 +127,25 @@ with gr.Blocks(css=css) as demo:
             with gr.Row():
                 width = gr.Slider(
                     label="Width",
-                    minimum=256,
+                    minimum=0,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=520,  # Replace with defaults that work for your model
+                    value=600,  # Replace with defaults that work for your model
                 )
 
                 height = gr.Slider(
                     label="Height",
-                    minimum=256,
+                    minimum=0,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=520,  # Replace with defaults that work for your model
+                    value=750,  # Replace with defaults that work for your model
                 )
 
             with gr.Row():
                 guidance_scale = gr.Slider(
                     label="Guidance scale",
                     minimum=0.0,
-                    maximum=10.0,
+                    maximum=1.0,
                     step=0.1,
                     value=0.0,  # Replace with defaults that work for your model
                 )