Update app.py

app.py

@@ -50,10 +50,17 @@ gallery = gr.Gallery(label="Generated images", show_label=False, elem_id="galler
 title="Whisper to Stable Diffusion"
 description="""
 <p style='text-align: center;'>
-This demo is running on CPU. Build by Sylvain <a href='https://twitter.com/fffiloni' target='_blank'>@fffiloni</a> • <img id='visitor-badge' alt='visitor badge' src='https://visitor-badge.glitch.me/badge?page_id=gradio-blocks.sd-img-variations' style='display: inline-block' />
-Record an audio description of an image, stop recording, then hit the Submit button to get 2 images from Stable Diffusion.
+This demo is running on CPU. Build by Sylvain <a href='https://twitter.com/fffiloni' target='_blank'>@fffiloni</a> • <img id='visitor-badge' alt='visitor badge' src='https://visitor-badge.glitch.me/badge?page_id=gradio-blocks.sd-img-variations' style='display: inline-block' /><br />
+Record an audio description of an image, stop recording, then hit the Submit button to get 2 images from Stable Diffusion.<br />
 Your audio will be translated to English through OpenAI's Whisper, then sent as a prompt to Stable Diffusion.
 Try it in French ! ;) 
 </p>
 """
+
+article="""
+<p style='text-align: center;'>
+Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification.<br />
+Model by <a href="https://github.com/openai/whisper" style="text-decoration: underline;" target="_blank">OpenAI</a>
+</p>
+"""
 gr.Interface(fn=get_images, inputs=audio, outputs=[translated_prompt, gallery], title=title, description=description).queue(max_size=1000).launch(enable_queue=True)