Set UI stuff

app.py

@@ -1,5 +1,6 @@
 from diffusers import DDPMPipeline
 import gradio as gr
+from ui import title, description, examples
 
 
 
@@ -10,11 +11,11 @@ models = [
 {'type': 'butterflies', 'res': 128, 'id': 'mrm8488/ddpm-ema-butterflies-128'},
 {'type': 'human_faces', 'res': 256, 'id': 'fusing/ddpm-celeba-hq'}
 ]
-
+'''
 for model in models:
     pipeline = DDPMPipeline.from_pretrained(model['id'])
     pipeline.save_pretrained(model['id'])
-
+'''
 def predict(type):
     model_id = None
     for model in models:
@@ -31,7 +32,9 @@ def predict(type):
 
 gr.Interface(
     predict,
-    inputs=[gr.components.Dropdown(choices = [model['type'] for model in models], label='Models')
+    inputs=[gr.components.Dropdown(choices = [model['type'] for model in models], label='Choose a model')
     ],
-    outputs=["image"]
+    outputs=["image"],
+    title=title,
+    description=description
 ).launch()

ui.py

@@ -0,0 +1,13 @@
+title = "DDPM Diffusion models trained on Q-Blocks Demo"
+description = """
+<p>
+<center>
+Demo of DDPM Diffusion models trained using <a href='https://github.com/huggingface/diffusers' target='_blank'>HF/Diffusers library</a> on 
+<a href='https://www.qblocks.cloud/' target='_blank'><b>Q-Blocks</b></a> hardware.
+<img src="https://raw.githubusercontent.com/huggingface/diffusers/main/docs/source/imgs/diffusers_library.jpg" alt="meta nllb pic" width="300"/>
+<img alt="Imagen" draggable="true" src="https://pbs.twimg.com/profile_images/1393401965653204992/onkaGwZO_400x400.jpg"  width="200">
+</center>
+</p>
+"""
+
+examples = []