Update app.py

app.py

@@ -23,7 +23,8 @@ print (API_KEY)
 title = "<h1><center>Markup-to-Image Diffusion Models with Scheduled Sampling</center></h1>"
 authors = "<center>Yuntian Deng, Noriyuki Kojima, Alexander M. Rush</center>"
 info = '<center><a href="https://openreview.net/pdf?id=81VJDmOE2ol">Paper</a> <a href="https://github.com/da03/markup2im">Code</a></center>'
-notice = "<p><center><strong>Notice:</strong> Due to resource constraints, we've transitioned from GPU to CPU processing for this demo, which results in significantly longer inference times. We appreciate your understanding.</center></p>"
+#notice = "<p><center><strong>Notice:</strong> Due to resource constraints, we've transitioned from GPU to CPU processing for this demo, which results in significantly longer inference times. We appreciate your understanding.</center></p>"
+notice = "<p><center><strong>Notice:</strong> This demo is powered by GPU resources generously supported by the Hugging Face Community Grant. Thank you, Hugging Face!</center></p>"
 
 
 # setup
@@ -66,7 +67,7 @@ with gr.Blocks() as demo:
     gr.Markdown(title)
     gr.Markdown(authors)
     gr.Markdown(info)
-    #gr.Markdown(notice)
+    gr.Markdown(notice)
     with gr.Row():
         with gr.Column(scale=2):
             textbox = gr.Textbox(label=r'Type LaTeX formula below and click "Generate"', lines=1, max_lines=1, placeholder='Type LaTeX formula here and click "Generate"', value=r'\sum_{t=1}^T\E_{y_t \sim {\tilde P(y_t| y_0)}} \left\| \frac{y_t - \sqrt{\bar{\alpha}_t}y_0}{\sqrt{1-\bar{\alpha}_t}} - \epsilon_\theta(y_t, t)\right\|^2.')