fix bench_df modifications

app.py

@@ -120,24 +120,26 @@ def get_benchmark_df(benchmark="1xA100-80GB"):
 
 def get_benchmark_table(bench_df):
     # add * to quantized models score
-    bench_df["best_score"] = bench_df.apply(
+    copy_df = bench_df.copy()
+
+    copy_df["best_score"] = copy_df.apply(
         lambda x: f"{x['best_score']}**" if x["quantized"] else x["best_score"],
         axis=1,
     )
 
     # sort
-    bench_df.sort_values(by=SORTING_COLUMN, ascending=True, inplace=True)
+    copy_df.sort_values(by=SORTING_COLUMN, ascending=True, inplace=True)
     # filter
-    bench_df = bench_df[list(ALL_COLUMNS_MAPPING.keys())]
+    copy_df = copy_df[list(ALL_COLUMNS_MAPPING.keys())]
     # rename
-    bench_df.rename(columns=ALL_COLUMNS_MAPPING, inplace=True)
+    copy_df.rename(columns=ALL_COLUMNS_MAPPING, inplace=True)
     # transform
-    bench_df["Type 🤗"] = bench_df["Type 🤗"].apply(process_model_type)
-    bench_df["Best Scored Model 🏆"] = bench_df["Best Scored Model 🏆"].apply(
+    copy_df["Type 🤗"] = copy_df["Type 🤗"].apply(process_model_type)
+    copy_df["Best Scored Model 🏆"] = copy_df["Best Scored Model 🏆"].apply(
         process_model_name
     )
 
-    return bench_df
+    return copy_df
 
 
 def get_benchmark_plot(bench_df):