updated GPTQ display!

app.py

@@ -253,14 +253,14 @@ def select_columns(df: pd.DataFrame, columns: list) -> pd.DataFrame:
 
 
 NUMERIC_INTERVALS = {
-    "Unknown": pd.Interval(-1, 0, closed="right"),
-    "0~1.5B": pd.Interval(0, 1.5, closed="right"),
-    "1.5~3B": pd.Interval(1.5, 3, closed="right"),
-    "3~7B": pd.Interval(3, 7, closed="right"),
-    "7~13B": pd.Interval(7, 13, closed="right"),
-    "13~35B": pd.Interval(13, 35, closed="right"),
-    "35~60B": pd.Interval(35, 60, closed="right"),
-    "60B+": pd.Interval(60, 10000, closed="right"),
+    "?": pd.Interval(-1, 0, closed="right"),
+    "0~1.5": pd.Interval(0, 1.5, closed="right"),
+    "1.5~3": pd.Interval(1.5, 3, closed="right"),
+    "3~7": pd.Interval(3, 7, closed="right"),
+    "7~13": pd.Interval(7, 13, closed="right"),
+    "13~35": pd.Interval(13, 35, closed="right"),
+    "35~60": pd.Interval(35, 60, closed="right"),
+    "60+": pd.Interval(60, 10000, closed="right"),
 }
 
 
@@ -378,7 +378,7 @@ with demo:
                             elem_id="filter-columns-precision",
                         )
                         filter_columns_size = gr.CheckboxGroup(
-                            label="Model sizes",
+                            label="Model sizes (in billions of parameters)",
                             choices=list(NUMERIC_INTERVALS.keys()),
                             value=list(NUMERIC_INTERVALS.keys()),
                             interactive=True,

model_info_cache.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:94e311e2414e80b8eb5e50844c2e79daa4bd3bb6be516fc2448bd05242d125f9
-size 3656702
+oid sha256:f98e18ea0fcf11737e108f966f6d8b09120c6a2c231b70e9e242e9bba3145a47
+size 3780284

model_size_cache.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4aedc91b51cf257cbe3e26a1fdd99e19250bacfa619a64dd85e67d4ff383130f
-size 75455
+oid sha256:ace7167a258f711fa7ffeaadddc6ebef8ccb92651dce8b805228c2f18c988958
+size 75324

src/display_models/get_model_metadata.py

@@ -45,13 +45,15 @@ def get_model_infos_from_hub(leaderboard_data: List[dict]):
                 model_data[AutoEvalColumn.license.name] = None
                 model_data[AutoEvalColumn.likes.name] = None
                 if model_name not in model_size_cache:
-                    model_size_cache[model_name] = get_model_size(model_name, None)
+                    size_factor = 8 if model_data["Precision"] == "GPTQ" else 1
+                    model_size_cache[model_name] = size_factor * get_model_size(model_name, None)
                 model_data[AutoEvalColumn.params.name] = model_size_cache[model_name]
 
         model_data[AutoEvalColumn.license.name] = get_model_license(model_info)
         model_data[AutoEvalColumn.likes.name] = get_model_likes(model_info)
         if model_name not in model_size_cache:
-            model_size_cache[model_name] = get_model_size(model_name, model_info)
+            size_factor = 8 if model_data["Precision"] == "GPTQ" else 1
+            model_size_cache[model_name] = size_factor * get_model_size(model_name, model_info)
         model_data[AutoEvalColumn.params.name] = model_size_cache[model_name]
 
     # save cache to disk in pickle format

src/display_models/read_results.py

@@ -81,6 +81,8 @@ def parse_eval_result(json_filepath: str) -> Tuple[str, list[dict]]:
     model_split = model.split("/", 1)
 
     precision = config.get("model_dtype")
+    if precision == "None":
+        precision = "GPTQ"
 
     model = model_split[-1]