Update app.py

app.py

@@ -467,29 +467,19 @@ with gr.Blocks(
     gr.Markdown(
         """# <span style='color:var(--primary-500)!important'>Beam Search Visualizer</span>
 
-Play with the parameters below to understand how beam search decoding works!
-
-Here's GPT2 doing beam search decoding for you.
-
-#### <span style='color:var(--primary-500)!important'>Parameters:</span>
-- **Sentence to decode from** (`inputs`): the input sequence to your decoder.
-- **Number of steps** (`max_new_tokens`): the number of tokens to generate.
-- **Number of beams** (`num_beams`): the number of beams to use.
-- **Length penalty** (`length_penalty`): the length penalty to apply to outputs. `length_penalty` > 0.0 promotes longer sequences, while `length_penalty` < 0.0 encourages shorter sequences.
-This parameter will not impact the beam search paths, but only influence the choice of sequences in the end towards longer or shorter sequences.
-- **Number of return sequences** (`num_return_sequences`): the number of sequences to be returned at the end of generation. Should be `<= num_beams`.
+Author: Aymeric Roucher
 """
     )
     text = gr.Textbox(
-        label="Sentence to decode from",
-        value="Conclusion: thanks a lot. That's all for today",
+        label="Prompt",
+        value="Baking a cake is easy. First, you need to",
     )
     with gr.Row():
         n_steps = gr.Slider(
-            label="Number of steps", minimum=1, maximum=12, step=1, value=5
+            label="Number of tokens", minimum=1, maximum=24, step=1, value=12
         )
         n_beams = gr.Slider(
-            label="Number of beams", minimum=1, maximum=4, step=1, value=4
+            label="Beam size", minimum=1, maximum=4, step=1, value=4
         )
 
     button = gr.Button()