Update app.py

app.py

@@ -10,25 +10,13 @@ if torch.cuda.is_available():
 else:
     pipe_vq = DiffusionPipeline.from_pretrained("microsoft/vq-diffusion-ithq")
 
-examples = [
-  ["An astronaut riding a horse."],
-  ["A teddy bear playing in the water."],
-  ["A simple wedding cake with lego bride and groom topper and cake pops."],
-  ["A realistic tree using a mixture of different colored pencils."],
-  ["Muscular Santa Claus."],
-  ["A man with a pineapple head."],
-  ["Pebble tower standing on the left on the sea beach."],
-]
-
 title = "VQ Diffusion vs. Stable Diffusion 1-5"
 description = "[VQ-Diffusion-ITHQ](https://huggingface.co/microsoft/vq-diffusion-ithq) for text to image generation."
 
-
 def inference(text):
     output_vq_diffusion = pipe_vq(text, truncation_rate=0.86).images[0]
     return output_vq_diffusion
 
-
 io = gr.Interface(
   inference,
   gr.Textbox(lines=3),
@@ -36,7 +24,6 @@ io = gr.Interface(
     gr.Image(type="pil", label="VQ-Diffusion"),
   ],
   title=title,
-  description=description,
-  examples=examples
+  description=description
 )
 io.launch()