Update app.py

app.py

@@ -183,7 +183,7 @@ with gr.Blocks(css=css) as demo:
                         minimum=0.0,
                         maximum=10.0,
                         step=0.1,
-                        value=0.0, #Replace with defaults that work for your model
+                        value=7.5, #Replace with defaults that work for your model
                     )
                     
                     num_inference_steps = gr.Slider(
@@ -191,7 +191,7 @@ with gr.Blocks(css=css) as demo:
                         minimum=1,
                         maximum=50,
                         step=1,
-                        value=2, #Replace with defaults that work for your model
+                        value=25, #Replace with defaults that work for your model
                     )
             
             gr.Examples(
@@ -201,7 +201,7 @@ with gr.Blocks(css=css) as demo:
     
             run_button.click(
                 fn=infer_t2i,
-                inputs = [prompt, model_choice, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
+                inputs = [model_choice, prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
                 outputs = [result, seed]
             )
 
@@ -300,7 +300,7 @@ with gr.Blocks(css=css) as demo:
     
             run_button.click(
                 fn=infer_i2i,
-                inputs = [prompt, model_choice, image_upload_input, editing_strength, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
+                inputs = [model_choice, prompt, image_upload_input, editing_strength, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
                 outputs = [result, seed]
             )
 
@@ -399,7 +399,7 @@ with gr.Blocks(css=css) as demo:
     
             run_button.click(
                 fn=infer_ip_adapter,
-                inputs = [prompt, model_choice, image_upload_input, ip_adapter_scale, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
+                inputs = [model_choice, prompt, image_upload_input, ip_adapter_scale, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
                 outputs = [result, seed]
             )