cjj-table

app.py

@@ -291,15 +291,15 @@ This leaderboard is used to show the performance of the <strong>automatic evalua
         for j in range(len(metric)): # 每种指标
             index = f"{metric[j]} ({task[i]})"
             df[index] = d[metric[j]]
-            for k in range(len[df["TeamId"]]):
+            for k in range(len(df["TeamId"])):
                 total[k] += d[metric[j]][k]
         average_index = f"Average ({task[i]})"
         df[average_index] = [k / len(metric) for k in total]
-        for k in range(len[df["TeamId"]]):
+        for k in range(len(df["TeamId"])):
             overall_total[k] += df[average_index][k]
 
     df["Average (all 4 datatsets)"] = [k / len(task) for k in overall_total]
-    
+
     st.dataframe(pd.DataFrame(df), use_container_width=True)
     st.markdown("A baseline example can be found in the [baseline_example](https://huggingface.co/spaces/THUIR/AEOLLM/tree/main/baseline_example) folder.")
     # 获取北京时间