found it

app.py

@@ -88,7 +88,10 @@ def get_benchmark_df(benchmark="Succeeded-1xA100-80GB"):
         "generate.energy_consumption(kWh/token)"
     ].fillna(1)
     # fix nan values
-    merged_df[merged_df["generate.energy_consumption(tokens/kWh)"] == 1] = "N/A"
+    merged_df[
+        merged_df["generate.energy_consumption(tokens/kWh)"] == 1,
+        "generate.energy_consumption(tokens/kWh)",
+    ] = "N/A"
     # add optimizations
     merged_df["optimizations"] = merged_df["backend.bettertransformer"].apply(
         lambda x: "BetterTransformer" if x else "None"
@@ -128,9 +131,6 @@ def get_benchmark_table(bench_df):
 def get_benchmark_chart(bench_df):
     copy_df = bench_df.copy()
     # filter latency bigger than 100s
-    copy_df["generate.latency(s)"] = copy_df["generate.latency(s)"].apply(
-        lambda x: x if isinstance(x, (int, float)) else 1000
-    )
     copy_df = copy_df[copy_df["generate.latency(s)"] <= 100]
     # rename model_type
     copy_df["model_type"] = copy_df["model_type"].apply(process_model_type)