Update app.py

app.py

@@ -19,7 +19,7 @@ STYLE = """
 	display: grid;
 	align-items: center;
     margin: 0!important;
-    overflow: auto;
+    overflow-y: hidden;
 }
 .prose ul ul {
     font-size: 10px!important;
@@ -352,7 +352,7 @@ def generate_beams(start_sentence, scores, sequences, length_penalty):
                 cumulative_score=cumulative_score,
                 total_score=cumulative_score
                 / ((input_length + step - 1) ** length_penalty),
-                children_score_divider=((input_length + step + 1) ** length_penalty),
+                children_score_divider=((input_length + step) ** length_penalty),
                 is_final=(
                     step == len(scores) - 1
                     or current_token_choice_ix == tokenizer.eos_token_id
@@ -379,7 +379,6 @@ def generate_beams(start_sentence, scores, sequences, length_penalty):
         for beam_ix in range(n_beams):
             current_token_choice_ix = top_df_selected.iloc[beam_ix]["token_index"]
             beam_trees[beam_ix] = beam_trees[beam_ix].children[current_token_choice_ix]
-    print("Final nodes", candidate_nodes)
 
     return original_tree
 
@@ -443,7 +442,7 @@ Play with the parameters below to understand how beam search decoding works!
             label="Number of beams", minimum=2, maximum=4, step=1, value=3
         )
         length_penalty = gr.Slider(
-            label="Length penalty", minimum=-4, maximum=4, step=0.5, value=1
+            label="Length penalty", minimum=-3, maximum=3, step=0.5, value=1
         )
     button = gr.Button()
     out_html = gr.Markdown()