Update app.py

app.py

@@ -192,17 +192,19 @@ with gr.Blocks(theme=gr.themes.Default(), css=css) as demo:
                 We will follow the SelfIE implementation in this space for concreteness. Patchscopes are so general that they encompass many other interpretation techniques too!!! 
             ''', line_breaks=True)
             
-            gr.Markdown('**👾 The idea is really simple: models are able to understand their own hidden states by nature! 👾**',
-                          # elem_classes=['explanation_accordion']
-                        )  
+            # gr.Markdown('**👾 The idea is really simple: models are able to understand their own hidden states by nature! 👾**',
+            #               # elem_classes=['explanation_accordion']
+            #             )  
             gr.Markdown(
-            '''According to the residual stream view ([nostalgebraist, 2020](https://www.lesswrong.com/posts/AcKRB8wDpdaN6v6ru/interpreting-gpt-the-logit-lens)), internal representations from different layers are transferable between layers. 
+            '''
+            **👾 The idea is really simple: models are able to understand their own hidden states by nature! 👾**
+            According to the residual stream view ([nostalgebraist, 2020](https://www.lesswrong.com/posts/AcKRB8wDpdaN6v6ru/interpreting-gpt-the-logit-lens)), internal representations from different layers are transferable between layers. 
             So we can inject an representation from (roughly) any layer to any layer! If I give a model a prompt of the form ``User: [X] Assistant: Sure'll I'll repeat your message`` and replace the internal representation of ``[X]`` *during computation* with the hidden state we want to understand, 
             we expect to get back a summary of the information that exists inside the hidden state. Since the model uses a roughly common latent space, it can understand representations from different layers and different runs!! How cool is that! 😯😯😯
             ''', line_breaks=True)
                 
-        with gr.Column(scale=1):    
-            gr.Markdown('<span style="font-size:180px;">🤔</span>')
+        # with gr.Column(scale=1):    
+        #     gr.Markdown('<span style="font-size:180px;">🤔</span>')
 
     with gr.Group('Interpretation'):
         interpretation_prompt = gr.Text(suggested_interpretation_prompts[0], label='Interpretation Prompt')
@@ -233,7 +235,7 @@ with gr.Blocks(theme=gr.themes.Default(), css=css) as demo:
     use_gpu = False # gr.Checkbox(value=False, label='Use GPU')
     progress_dummy = gr.Markdown('', elem_id='progress_dummy')
 
-    interpretation_bubbles = [gr.Textbox('', container=False, visible=False, elem_classes=['bubble', 
+    interpretation_bubbles = [gr.Textbox('', label=f'Layer {i}', container=False, visible=False, elem_classes=['bubble', 
                                                                                            'even_bubble' if i % 2 == 0 else 'odd_bubble'])
                              for i in range(model.config.num_hidden_layers)]