Update app.py

app.py

@@ -1,5 +1,5 @@
 import os
-os.system('pip install gradio==2.3.0a0')
+#os.system('pip install gradio==2.3.0a0')
 os.system('pip freeze')
 import torch
 torch.hub.download_url_to_file('https://heibox.uni-heidelberg.de/d/a7530b09fed84f80a887/files/?p=%2Fconfigs%2Fmodel.yaml&dl=1', 'vqgan_imagenet_f16_16384.yaml')
@@ -366,7 +366,7 @@ def load_image( infilename ) :
     data = np.asarray( img, dtype="int32" )
     return data
 title = "VQGAN + CLIP"
-description = "Gradio demo for VQGAN + CLIP. To use it, simply add your text, or click one of the examples to load them. Read more at the links below. Please click submit only once. Results will show up in under a minute."
+description = "Gradio demo for VQGAN + CLIP. To use it, simply add your text, or click one of the examples to load them. Read more at the links below."
 article = "<p style='text-align: center'>Originally made by Katherine Crowson (https://github.com/crowsonkb, https://twitter.com/RiversHaveWings). The original BigGAN+CLIP method was by https://twitter.com/advadnoun. Added some explanations and modifications by Eleiber#8347, pooling trick by Crimeacs#8222 (https://twitter.com/EarthML1) and the GUI was made with the help of Abulafia#3734. | <a href='https://colab.research.google.com/drive/1ZAus_gn2RhTZWzOWUpPERNC0Q8OhZRTZ'>Colab</a> | <a href='https://github.com/CompVis/taming-transformers'>Taming Transformers Github Repo</a> | <a href='https://github.com/openai/CLIP'>CLIP Github Repo</a> | Special thanks to BoneAmputee (https://twitter.com/BoneAmputee) for suggestions and advice</p>"
 gr.Interface(
     inference,