test

src/display/utils.py

@@ -36,7 +36,7 @@ auto_eval_column_dict.append(["architecture", ColumnContent, ColumnContent("Arch
 auto_eval_column_dict.append(["weight_type", ColumnContent, ColumnContent("Weight type", "str", False, True)])
 auto_eval_column_dict.append(["precision", ColumnContent, ColumnContent("Precision", "str", False)])
 auto_eval_column_dict.append(["license", ColumnContent, ColumnContent("Hub License", "str", False)])
-auto_eval_column_dict.append(["params", ColumnContent, ColumnContent("#Params (B)", "number", False)])
+auto_eval_column_dict.append(["params", ColumnContent, ColumnContent("#Params (B)", "float", False)])
 auto_eval_column_dict.append(["likes", ColumnContent, ColumnContent("Hub ❤️", "number", False)])
 auto_eval_column_dict.append(["still_on_hub", ColumnContent, ColumnContent("Available on the hub", "bool", False)])
 auto_eval_column_dict.append(["revision", ColumnContent, ColumnContent("Model sha", "str", False, False)])

src/leaderboard/read_evals.py

@@ -40,13 +40,14 @@ class EvalResult:
 
         config = data.get("config")
 
-        # Precision
+        # Precision #1
         precision = Precision.from_str(config.get("model_dtype"))
 
-        # Get model and org
+        # Get model and org 
         org_and_model = config.get("model_name", config.get("model_args", None))
         org_and_model = org_and_model.split("/", 1)
 
+        # 如果model_name = “”
         if len(org_and_model) == 1:
             org = None
             model = org_and_model[0]
@@ -114,8 +115,8 @@ class EvalResult:
         #average = next(iter(self.results.values()))
         data_dict = {
             "eval_name": self.eval_name,  # not a column, just a save name,
-            AutoEvalColumn.precision.name: self.precision.value.name,
-            AutoEvalColumn.model_type.name: self.model_type.value.name,
+            AutoEvalColumn.precision.name: self.precision.value.name,   #results/precision
+            AutoEvalColumn.model_type.name: self.model_type.value.name,  #requests/model_type
             AutoEvalColumn.model_type_symbol.name: self.model_type.value.symbol,
             AutoEvalColumn.weight_type.name: self.weight_type.value.name,
             AutoEvalColumn.architecture.name: self.architecture,

src/populate.py

@@ -13,7 +13,8 @@ def get_leaderboard_df(results_path: str, requests_path: str, cols: list, benchm
     raw_data = get_raw_eval_results(results_path, requests_path)
 
     all_data_json = [v.to_dict() for v in raw_data]
-
+    print(all_data_json)
+    assert 0
     df = pd.DataFrame.from_records(all_data_json)
 
     df = df.sort_values(by=[AutoEvalColumn.task0.name], ascending=False)