Update app.py

app.py

@@ -255,16 +255,12 @@ def generate_beams(start_sentence, scores, sequences, beam_indices):
         top_df_selected = top_df.sort_values("cumulative_score", ascending=False).iloc[
             :n_beams
         ]
-        print(step)
-        display(top_df_selected)
 
         # Write the scores table - one per beam source?
         # Edge case: if several beam indexes are actually on the same beam, the selected tokens by beam_index for the second one will be empty. So we reverse
         for beam_ix in reversed(list(range(n_beams))):
             current_beam = beam_trees[beam_ix]
             selected_tokens = top_df_selected.loc[top_df_selected["beam_index"] == beam_ix]
-            print(step, beam_ix)
-            display(selected_tokens)
             markdown_table = generate_markdown_table(
                 step_scores[beam_ix, :],
                 current_beam.cumulative_score,