Removed unnecessary columns from the table.

src/display/utils.py

@@ -41,14 +41,14 @@ for task in Tasks:
 
 # Model information
 #auto_eval_column_dict.append(["model_type", ColumnContent, ColumnContent("Type", "str", False)])
-auto_eval_column_dict.append(["architecture", ColumnContent, ColumnContent("Architecture", "str", False)])
-auto_eval_column_dict.append(["weight_type", ColumnContent, ColumnContent("Weight type", "str", False, True)])
+#auto_eval_column_dict.append(["architecture", ColumnContent, ColumnContent("Architecture", "str", False)])
+#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(["license", ColumnContent, ColumnContent("Hub License", "str", False)])
 auto_eval_column_dict.append(["params", ColumnContent, ColumnContent("#Params (B)", "number", 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)])
+#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)])
 #auto_eval_column_dict.append(["submitted_time", ColumnContent, ColumnContent("Submitted time", "date", False)])
 
 # We use make dataclass to dynamically fill the scores from Tasks
@@ -58,11 +58,11 @@ AutoEvalColumn = make_dataclass("AutoEvalColumn", auto_eval_column_dict, frozen=
 @dataclass(frozen=True)
 class EvalQueueColumn:  # Queue column
     model = ColumnContent("model", "markdown", True)
-    revision = ColumnContent("revision", "str", True)
-    private = ColumnContent("private", "bool", True)
+    #revision = ColumnContent("revision", "str", True)
+    #private = ColumnContent("private", "bool", True)
     #precision = ColumnContent("precision", "str", True)
-    weight_type = ColumnContent("weight_type", "str", "Original")
-    status = ColumnContent("status", "str", True)
+    #weight_type = ColumnContent("weight_type", "str", "Original")
+    #status = ColumnContent("status", "str", True)
 
 ## All the model information that we might need
 @dataclass

src/leaderboard/read_evals.py

@@ -23,19 +23,19 @@ class EvalResult:
     full_model: str # org/model (path on hub)
     org: str 
     model: str
-    revision: str # commit hash, "" if main
+    #revision: str # commit hash, "" if main
     #submitted_time: datetime
     results: Dict[str, Union[float, int]]  # float o int
     average_CPS: float
     is_5fewshot: bool
     fewshot_symbol: FewShotType = FewShotType.Unknown
-    weight_type: WeightType = WeightType.Original # Original or Adapter
-    architecture: str = "Unknown" 
-    license: str = "?"
-    likes: int = 0
+    #weight_type: WeightType = WeightType.Original # Original or Adapter
+    #architecture: str = "Unknown"
+    #license: str = "?"
+    #likes: int = 0
     num_params: int = 0
     date: str = "" # submission date of request file
-    still_on_hub: bool = False
+    #still_on_hub: bool = False
     rank: int = 0#str = field(default=0)  # nuovo campo con default = 0
     size_symbol: SizeType = SizeType.Unknown
 
@@ -123,9 +123,9 @@ class EvalResult:
             average_CPS=average_CPS,
             fewshot_symbol=fewshot_symbol,
             is_5fewshot=is_5fewshot,
-            revision= config.get("model_sha", ""),
-            still_on_hub=still_on_hub,
-            architecture=architecture,
+            #revision= config.get("model_sha", ""),
+            #still_on_hub=still_on_hub,
+            #architecture=architecture,
             num_params=num_params,
             rank = rank,
             size_symbol=size_symbol
@@ -170,16 +170,16 @@ class EvalResult:
             #AutoEvalColumn.model_type.name: self.model_type.value.name if self.model_type else "Unknown",
             #AutoEvalColumn.model_type_symbol.name: self.model_type.value.symbol if self.model_type else "Unknown",
             AutoEvalColumn.fewshot_symbol.name: fewshot_symbol,
-            AutoEvalColumn.weight_type.name: self.weight_type.value.name,
-            AutoEvalColumn.architecture.name: self.architecture,
+            #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.revision.name: self.revision,
             AutoEvalColumn.average.name: average,
             AutoEvalColumn.is_5fewshot.name: self.is_5fewshot,
-            AutoEvalColumn.license.name: self.license,
-            AutoEvalColumn.likes.name: self.likes,
+            #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,
+            #AutoEvalColumn.still_on_hub.name: self.still_on_hub,
             AutoEvalColumn.rank.name: self.rank,
             AutoEvalColumn.size_symbol.name: size_symbol
         }