added * to quantized models scores

app.py

@@ -27,6 +27,10 @@ LLM_PERF_DATASET_REPO = "optimum/llm-perf-dataset"
 OPTIMUM_TOKEN = os.environ.get("OPTIMUM_TOKEN", None)
 
 
+TRUE_WEIGHT_CLASSES = {
+    "6B": "7B",
+}
+
 ALL_COLUMNS_MAPPING = {
     "model_type": "Type 🤗",
     "weight_class": "Class 🏋️",
@@ -100,10 +104,14 @@ def get_benchmark_df(benchmark="1xA100-80GB"):
     merged_df["tradeoff"] = (score_distance**2 + latency_distance**2) ** 0.5
     merged_df["tradeoff"] = merged_df["tradeoff"].round(2)
 
-    # remove score for quantized models
+    # add * to quantized models
     merged_df.loc[
         merged_df["optimizations"].str.contains("LLM.int8|LLM.fp4"), "best_score"
-    ] = "Not Evaluated"
+    ] = merged_df.loc[
+        merged_df["optimizations"].str.contains("LLM.int8|LLM.fp4"), "best_score"
+    ].apply(
+        lambda x: f"{x}*"
+    )
 
     return merged_df