changing the text

app.py

@@ -104,22 +104,23 @@ def predict(prompt, weights, seed, scale=7.5, steps=50):
 
 
 MESSAGE = '''
-### Welcome to Our Negative Prompt Implementation!
-
 Our method helps you achieve two amazing things:
 
 1. Edit your generated images iteratively without damaging any important concepts.
 2. Generate any view of objects that the original Stable Diffusion implementation couldn't produce. For example, you can generate a "peacock, back view" by using "peacock, front view" as the negative prompt. Compare our method to [Stable Diffusion](https://huggingface.co/spaces/stabilityai/stable-diffusion).
 
-Unlike the original implementation, our method ensures that everything provided as the main prompt remains intact even when there is an overlap between the positive and negative prompts.
-
-We've also integrated the idea of robust view generation in text-to-3D to avoid the multihead problem. Check out our work on this at [perp-neg.github.io](https://perp-neg.github.io/).
-
 To use our demo, simply enter your main prompt first, followed by a set of positive and negative prompts separated by "|". When only one prompt is provided and the weight of that prompt is 1, it is identical to using Stable Diffusion. We provided those as examples for the sake of comparison of our algorithm to Stable Diffusion. Put the weight of main prompt as 1.
 
 Use our demo to create some amazing and unique images!
 '''
 
+MESSAGE_END = '''
+
+Unlike the original implementation, our method ensures that everything provided as the main prompt remains intact even when there is an overlap between the positive and negative prompts.
+
+We've also integrated the idea of robust view generation in text-to-3D to avoid the multihead problem. Check out our work on this at [perp-neg.github.io](https://perp-neg.github.io/).
+
+'''
 
 app = gr.Blocks()
 with app:
@@ -176,8 +177,9 @@ with app:
         outputs=[img_output],
     )
     gr.Markdown("""
-    \n The algorithem is based on the paper: [Re-imagine the Negative Prompt Algorithm: Transform 2D Diffusion into 3D, alleviate Janus problem and Beyond.](https://Perp-Neg.github.io).
-    """)    
+    \n The algorithem is based on the paper: [Re-imagine the Negative Prompt Algorithm: Transform 2D Diffusion into 3D, alleviate Janus problem and Beyond.](https://Perp-Neg.github.io)
+    """)
+    gr.Markdown(MESSAGE_END)       
 
     gr.Markdown(
         """