Remove n-best list

app.py

@@ -435,19 +435,8 @@ def get_beam_search_html(
         output_scores=True,
         do_sample=False,
     )
-    markdown = "The conclusive sequences are the ones that end in an `<|endoftext|>` token or at the end of generation."
-    markdown += "\n\nThey are ranked by their scores, as given by the formula `score = cumulative_score / (output_length ** length_penalty)`.\n\n"
-    markdown += "Only the top `num_beams` scoring sequences are returned: in the tree they are highlighted in **<span style='color:var(--secondary-500)!important'>blue</span>**."
-    markdown += " The non-selected sequences are also shown in the tree, highlighted in **<span style='color:var(--primary-500)!important'>yellow</span>**."
-    markdown += "\n#### <span style='color:var(--secondary-500)!important'>Output sequences:</span>"
-    # Sequences are padded anyway so you can batch decode them
     decoded_sequences = tokenizer.batch_decode(outputs.sequences)
-
-    if number_beams > 1:
-        for i, sequence in enumerate(decoded_sequences):
-            markdown += f"\n- Score `{outputs.sequences_scores[i]:.2f}`: `{clean(sequence.replace('<s> ', ''))}`"
-    else:
-        markdown += f"\n- `{clean(decoded_sequences[0].replace('<s> ', ''))}`"
+    markdown = ""
 
     if number_beams > 1:
         original_tree = generate_beams(