fix

app.py

@@ -101,19 +101,11 @@ def get_benchmark_df(benchmark="Succeeded-1xA100-80GB"):
     merged_df.sort_values(by=SORTING_COLUMN, ascending=SORTING_ASCENDING, inplace=True)
     # drop duplicates
     merged_df.drop_duplicates(subset=NO_DUPLICATES_COLUMNS, inplace=True)
-    merged_df = merged_df[[*list(ALL_COLUMNS_MAPPING.keys()), "generate.latency(s)"]]
     return merged_df
 
 
 def get_benchmark_table(bench_df):
     copy_df = bench_df.copy()
-    # adding ** to quantized models score since we can't garantee the score is the same
-    copy_df["best_score"] = copy_df.apply(
-        lambda x: f"{x['best_score']}**"
-        if x["backend.quantization_strategy"] in ["bnb", "gptq"]
-        else x["best_score"],
-        axis=1,
-    )
     # filter
     copy_df = copy_df[list(ALL_COLUMNS_MAPPING.keys())]
     # rename
@@ -123,7 +115,13 @@ def get_benchmark_table(bench_df):
     copy_df["Best Scored LLM 🏆"] = copy_df["Best Scored LLM 🏆"].apply(
         process_model_name
     )
-
+    # process quantization
+    copy_df["Best Score (%) ⬆️"] = copy_df.apply(
+        lambda x: f"{x['Best Score (%) ⬆️']}**"
+        if x["Quantization 🗜️"] in ["BnB.4bit", "GPTQ.4bit"]
+        else x["Best Score (%) ⬆️"],
+        axis=1,
+    )
     return copy_df