Update app.py

app.py

@@ -287,6 +287,6 @@ examples = [[examples_1, 'GLIDE'], [examples_2, 'GLIDE'], [examples_3, 'CLEVR Ob
 
 import gradio as gr
 gr.Interface(title='Compositional Visual Generation with Composable Diffusion Models', 
-    description='<p>Demo for Composable Diffusion (~20s per example)</p><p>See more information from our <a href="https://energy-based-model.github.io/Compositional-Visual-Generation-with-Composable-Diffusion-Models/">Project Page</a>.</p><ul><li>One version is based on the released <a href="https://github.com/openai/glide-text2im">GLIDE</a> for composing natural language description.</li><li>Another is based on our pre-trained CLEVR Object Model for composing objects. <br>(<b>Note</b>: We recommend using <b><i>x</i></b> in range <b><i>[0.1, 0.9]</i></b> and <b><i>y</i></b> in range <b><i>[0.25, 0.7]</i></b>, since the training dataset labels are in given ranges.).</li></ul><p>When composing  multiple sentences, use `|` as the delimiter, see given examples below.</p>',
+    description='<p>Demo for Composable Diffusion (~20s per example)</p><p>See more information from our <a href="https://energy-based-model.github.io/Compositional-Visual-Generation-with-Composable-Diffusion-Models/">Project Page</a>.</p><ul><li>One version is based on the released <a href="https://github.com/openai/glide-text2im">GLIDE</a> for composing natural language description.</li><li>Another is based on our pre-trained CLEVR Object Model for composing objects. <br>(<b>Note</b>: We recommend using <b><i>x</i></b> in range <b><i>[0.1, 0.9]</i></b> and <b><i>y</i></b> in range <b><i>[0.25, 0.7]</i></b>, since the training dataset labels are in given ranges.)</li></ul><p>When composing  multiple sentences, use `|` as the delimiter, see given examples below.</p>',
     fn=compose, inputs=['text', gr.inputs.Radio(['GLIDE','CLEVR Objects'], type="value", default='GLIDE', label='version')], outputs='image', examples=examples).launch();