add fixed inference steps and title

app.py

@@ -51,7 +51,7 @@ scheduler_vibrant.config.original_inference_steps = 4
 
 
 @spaces.GPU
-def process_image(model_choice, num_images, height, width, prompt, seed):
+def process_image(model_choice, num_images, height, width, prompt, seed, inference_steps):
     global pipe
     # Switch to the selected model
     if model_choice == "NitroSD-Realism":
@@ -67,7 +67,7 @@ def process_image(model_choice, num_images, height, width, prompt, seed):
         return pipe(
             prompt=[prompt] * num_images,
             generator=torch.manual_seed(int(seed)),
-            num_inference_steps=1,
+            num_inference_steps=inference_steps,
             guidance_scale=0.0,
             height=int(height),
             width=int(width),
@@ -79,6 +79,9 @@ with gr.Blocks() as demo:
     with gr.Column():
         with gr.Row():
             with gr.Column():
+                gr.Markdown("""
+                    ### NitroFusion Single-Step Text-To-Image
+                """)
                 model_choice = gr.Dropdown(
                     label="Choose Model",
                     choices=["NitroSD-Realism", "NitroSD-Vibrant"],
@@ -96,11 +99,16 @@ with gr.Blocks() as demo:
                 )
                 prompt = gr.Text(label="Prompt", value="a photo of a cat", interactive=True)
                 seed = gr.Number(label="Seed", value=2024, interactive=True)
+                inference_steps = gr.Number(label="Inference Steps", value=1, interactive=False)
                 btn = gr.Button(value="Generate Image")
             with gr.Column():
                 output = gr.Gallery(height=1024)
 
-            btn.click(process_image, inputs=[model_choice, num_images, height, width, prompt, seed], outputs=[output])
+            btn.click(
+                process_image,
+                inputs=[model_choice, num_images, height, width, prompt, seed, inference_steps],
+                outputs=[output],
+            )
 
 if __name__ == "__main__":
     demo.launch()