Update app.py

app.py

@@ -3,7 +3,7 @@ from diffusers import DiffusionPipeline
 from PIL import Image
 import numpy as np
 
-pipeline = DiffusionPipeline.from_pretrained("Qilex/neoGen2")
+pipeline = DiffusionPipeline.from_pretrained("Qilex/VirtualPet-Gen")
 
 def generate_pets(num_to_generate):
     images = pipeline(num_to_generate)["sample"]
@@ -35,6 +35,8 @@ description = """
 This AI will 'dream' you up a virtual pet.
 \nThis is a denoising diffusion model trained in 48 hours for a hackathon, so the images can be pretty wonky.
 \nImages are 128x128px.
+
+\nBecause gradio isn't giving me a GPU, it takes 10-15 minutes to generate an image. Quick inference can be run in the <a href="https://colab.research.google.com/drive/19QtPOHv6HCpexyCMGXowX4vyZlF4ZZYN?usp=sharing">colab notebook</a>
 """
 article = '''Here's a gallery of some of the better pets:
 <div style="display: flex; justify-content:space-evenly">