Attempts to tweak the UI.

Brief description of the process.
Link to report.


Former-commit-id: 6976c64d585a732f04203bbdd8bf0a96282e0cae

app/ui_gradio.py

@@ -43,21 +43,42 @@ def top_k_predictions(prompt, num_candidates=32, k=8):
 def run_inference(prompt, num_images=32, num_preds=8):
     images = top_k_predictions(prompt, num_candidates=num_images, k=num_preds)
     predictions = compose_predictions(images)
-    output_title = 'This would be an html string to serve as title for the outputs.'
-    output_description = 'This is another random piece of html'
+    output_title = f"""
+    <p style="font-size:22px; font-style:bold">Best predictions</p>
+    <p>We asked our model to generate 32 candidates for your prompt:</p>
+
+    <pre>
+
+    <b>{prompt}</b>
+    </pre>
+    <p>We then used a pre-trained CLIP model to score them according to the
+    similarity of their text and image representations.</p>
+
+    <p>This is the result:</p>
+    """
+    output_description = """
+    <p>Read more about the process <a href="https://wandb.ai/dalle-mini/dalle-mini/reports/DALL-E-mini--Vmlldzo4NjIxODA">in our report</a>.<p>
+    <p style='text-align: center'>Created with <a href="https://github.com/borisdayma/dalle-mini">DALLE·mini</a></p>
+    """
     return (output_title, predictions, output_description)
 
 outputs = [
     gr.outputs.HTML(label=""),      # To be used as title
-    gr.outputs.Image(label='Top predictions'),
+    gr.outputs.Image(label=''),
     gr.outputs.HTML(label=""),      # Additional text that appears in the screenshot
 ]
 
+description = """
+Welcome to our demo of DALL·E-mini. This project was created on TPU v3-8s during the 🤗 Flax / JAX Community Week.
+It reproduces the essential characteristics of OpenAI's DALL·E, at a fraction of the size.
+
+Please, write what you would like the model to generate, or select one of the examples below.
+"""
 gr.Interface(run_inference, 
     inputs=[gr.inputs.Textbox(label='Prompt')], #, gr.inputs.Slider(1,64,1,8, label='Candidates to generate'), gr.inputs.Slider(1,8,1,1, label='Best predictions to show')], 
     outputs=outputs, 
     title='DALL·E mini',
-    description='This is a demo of the DALLE-mini model trained with Jax/Flax on TPU v3-8s during the HuggingFace Community Week',
+    description=description,
     article="<p style='text-align: center'> DALLE·mini by Boris Dayma et al. | <a href='https://github.com/borisdayma/dalle-mini'>GitHub</a></p>",
     layout='vertical',
     theme='huggingface',