Update app.py

app.py

@@ -388,14 +388,14 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css, title="PEEB") as demo:
     
     with gr.Column():
         title_text = gr.Markdown("# Demo | A classifier with Part-based Explainable and Editable Bottleneck (PEEB)")
-        gr.Markdown("Here is a PEEB bird classifier pre-trained on Bird-11K and finetuned on CUB-200 (see our [NAACL 2024 paper](https://arxiv.org/abs/2403.05297) and [code](https://github.com/anguyen8/peeb/tree/inspect_ddp)).\n This **interactive** demo shows how to run PEEB on an existing image and **edit** a class' textual description to update the classifier to detect one new bird species (without any re-training).")
+        gr.Markdown("PEEB is an image classifier, here for birds, pre-trained on Bird-11K and finetuned on CUB-200 (see our [NAACL 2024 paper](https://arxiv.org/abs/2403.05297) and [code](https://github.com/anguyen8/peeb/tree/inspect_ddp)).\n This **interactive** demo shows how to run PEEB on an existing image and how to **edit** a class' textual description to directly change the classifier to detect one new bird species (without any re-training).")
         gr.Markdown(
             """
-            Steps:
+            ### Steps:
             1. **Select an image**. Then, PEEB will show its grounded explanations and the top-1 predicted label with associated `softmax` confidence score.
             2. **Hover mouse over text descriptors** to see the corresponding region used to match to each text descriptor.
             3. **Edit the text under [Extra class]()** which correspond to one extra, new class (i.e. 200+1 = `201`). Further editing will overwrite this class' descriptors.
-            4. **Click on Predict** to see the grounded explanations and the top-1 label for the newly modified CUB-201 classifier.            
+            4. **Click on [Predict]()** to see the grounded explanations and the top-1 label for the newly modified CUB-201 classifier.            
             """
         )