Update app.py

app.py

@@ -14,7 +14,7 @@ else:
     torch_dtype = torch.float32
 
 MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 1024
+MAX_IMAGE_SIZE = 512
 
 
 # @spaces.GPU #[uncomment to use ZeroGPU]
@@ -67,12 +67,15 @@ css = """
 with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
         gr.Markdown(" # SD Demo")
+        gr.Markdown(" ## Inference Settings:")
+        gr.Markdown(" **roentgen**: - Inference Steps `75` - Guidance Scale: `4`")
+        gr.Markdown(" **sd2-findings**: - Inference Steps `35` - Guidance Scale: `7.5`")
 
         with gr.Row():
             model_repo_id = gr.Dropdown(
-                choices=['Cylumn/sd2-findings', 'Cylumn/sd2-report', 'Cylumn/sd3-report'],
+                choices=['Cylumn/roentgen', 'Cylumn/sd2-findings'],
                 label="Select Model",
-                value='Cylumn/sd3-report'
+                value='Cylumn/sd2-findings'
             )
 
         with gr.Row():
@@ -112,7 +115,7 @@ with gr.Blocks(css=css) as demo:
                     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(
@@ -126,16 +129,16 @@ with gr.Blocks(css=css) as demo:
             with gr.Row():
                 guidance_scale = gr.Slider(
                     label="Guidance scale",
-                    minimum=7.5,
+                    minimum=0,
                     maximum=10.0,
-                    step=0.1,
+                    step=0.5,
                     value=7.5,  # Replace with defaults that work for your model
                 )
 
                 num_inference_steps = gr.Slider(
                     label="Number of inference steps",
                     minimum=1,
-                    maximum=50,
+                    maximum=100,
                     step=1,
                     value=35,  # Replace with defaults that work for your model
                 )