add team name

app.py

@@ -81,7 +81,7 @@ def update_table(
     show_deleted: bool,
     query: str,
 ):
-    # filtered_df = filter_models(hidden_df, type_query, size_query, precision_query, show_deleted)
+    filtered_df = filter_models(hidden_df, type_query, size_query, precision_query, show_deleted)
     # filtered_df = filter_queries(query, filtered_df)
     df = select_columns(hidden_df, columns)
     return df
@@ -93,7 +93,7 @@ def search_table(df: pd.DataFrame, query: str) -> pd.DataFrame:
 
 def select_columns(df: pd.DataFrame, columns: list) -> pd.DataFrame:
     always_here_cols = [
-        AutoEvalColumn.model_type_symbol.name,
+        # AutoEvalColumn.model_type_symbol.name,
         AutoEvalColumn.model.name,
     ]
     # We use COLS to maintain sorting

src/display/utils.py

@@ -27,6 +27,9 @@ auto_eval_column_dict = []
 # Init
 # auto_eval_column_dict.append(["model_type_symbol", ColumnContent, ColumnContent("T", "str", True, never_hidden=True)])
 # auto_eval_column_dict.append(["model", ColumnContent, ColumnContent("Model", "markdown", True, never_hidden=True)])
+auto_eval_column_dict += [
+    ["team_name", ColumnContent, ColumnContent("Team", "str", True)],
+]
 # Scores
 auto_eval_column_dict.append(["average", ColumnContent, ColumnContent("Average ⬆️", "number", True)])
 for task in Tasks:

src/leaderboard/read_evals.py

@@ -111,17 +111,18 @@ class EvalResult:
 
     def to_dict(self):
         """Converts the Eval Result to a dict compatible with our dataframe display"""
+
         average = sum([v for v in self.results.values() if v is not None]) / len(Tasks)
+
         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.model_type_symbol.name: self.model_type.value.symbol,
+            AutoEvalColumn.team_name.name: self.team_name.value.name,
             # AutoEvalColumn.weight_type.name: self.weight_type.value.name,
             # AutoEvalColumn.architecture.name: self.architecture,
             # AutoEvalColumn.model.name: make_clickable_model(self.full_model),
             # AutoEvalColumn.revision.name: self.revision,
-            AutoEvalColumn.average.name: average,
+            # AutoEvalColumn.average.name: average,
             # AutoEvalColumn.license.name: self.license,
             # AutoEvalColumn.likes.name: self.likes,
             # AutoEvalColumn.params.name: self.num_params,
@@ -131,6 +132,22 @@ class EvalResult:
         for task in Tasks:
             data_dict[task.value.col_name] = self.results[task.value.benchmark]
 
+        # 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.model_type_symbol.name: self.model_type.value.symbol,
+        #     # AutoEvalColumn.weight_type.name: self.weight_type.value.name,
+        #     # AutoEvalColumn.architecture.name: self.architecture,
+        #     # AutoEvalColumn.model.name: make_clickable_model(self.full_model),
+        #     # AutoEvalColumn.revision.name: self.revision,
+        #     AutoEvalColumn.average.name: average,
+        #     # AutoEvalColumn.license.name: self.license,
+        #     # AutoEvalColumn.likes.name: self.likes,
+        #     # AutoEvalColumn.params.name: self.num_params,
+        #     # AutoEvalColumn.still_on_hub.name: self.still_on_hub,
+        # }
+
         return data_dict