Clémentine commited on
Commit
0c95215
1 Parent(s): 58860b6

updated display

Browse files
Files changed (2) hide show
  1. app.py +8 -2
  2. requirements.txt +1 -1
app.py CHANGED
@@ -41,6 +41,12 @@ def get_dataframe_from_results(eval_results, split):
41
  for i in [1, 2, 3]:
42
  local_df = local_df.rename_column(f"score_level{i}", f"Level {i} score (%)")
43
  df = pd.DataFrame(local_df)
 
 
 
 
 
 
44
  return df
45
 
46
  eval_dataframe_val = get_dataframe_from_results(eval_results=eval_results, split="validation")
@@ -172,7 +178,7 @@ with demo:
172
  value=CITATION_BUTTON_TEXT,
173
  label=CITATION_BUTTON_LABEL,
174
  elem_id="citation-button",
175
- ).style(show_copy_button=True)
176
 
177
  with gr.Tab("Results: Validation"):
178
  leaderboard_table_val = gr.components.Dataframe(
@@ -226,4 +232,4 @@ with demo:
226
  scheduler = BackgroundScheduler()
227
  scheduler.add_job(restart_space, "interval", seconds=3600)
228
  scheduler.start()
229
- demo.launch()
 
41
  for i in [1, 2, 3]:
42
  local_df = local_df.rename_column(f"score_level{i}", f"Level {i} score (%)")
43
  df = pd.DataFrame(local_df)
44
+ df = df.sort_values(by=["Average score (%)"], ascending=False)
45
+
46
+ numeric_cols = [c for c in local_df.column_names if "score" in c]
47
+ df[numeric_cols] = df[numeric_cols].multiply(100).round(decimals=2)
48
+ #df = df.style.format("{:.2%}", subset=numeric_cols)
49
+
50
  return df
51
 
52
  eval_dataframe_val = get_dataframe_from_results(eval_results=eval_results, split="validation")
 
178
  value=CITATION_BUTTON_TEXT,
179
  label=CITATION_BUTTON_LABEL,
180
  elem_id="citation-button",
181
+ ) #.style(show_copy_button=True)
182
 
183
  with gr.Tab("Results: Validation"):
184
  leaderboard_table_val = gr.components.Dataframe(
 
232
  scheduler = BackgroundScheduler()
233
  scheduler.add_job(restart_space, "interval", seconds=3600)
234
  scheduler.start()
235
+ demo.launch(debug=True)
requirements.txt CHANGED
@@ -1,5 +1,5 @@
1
  datasets==2.14.5
2
- gradio==3.41.0
3
  huggingface-hub==0.18.0
4
  numpy==1.24.2
5
  APScheduler==3.10.1
 
1
  datasets==2.14.5
2
+ gradio==4.1.1
3
  huggingface-hub==0.18.0
4
  numpy==1.24.2
5
  APScheduler==3.10.1