remove uneeded cols

src/display/utils.py

@@ -33,17 +33,15 @@ for task in Tasks:
     auto_eval_column_dict.append([task.name, ColumnContent, ColumnContent(task.value.col_name, "float", True)])
 # 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(["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(["params", ColumnContent, ColumnContent("#Params (B)", "float", False)])
 auto_eval_column_dict.append(["seq_length", ColumnContent, ColumnContent("Max Sequence Length", "number", False)])
-auto_eval_column_dict.append(
-    ["model_quantization_bits", ColumnContent, ColumnContent("Quantization Bits", "number", False)]
-)
+auto_eval_column_dict.append(["model_quantization_bits", ColumnContent, ColumnContent("Bits", "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(["still_on_hub", ColumnContent, ColumnContent("Available on the hub", "bool", False)])
 # auto_eval_column_dict.append(["revision", ColumnContent, ColumnContent("Model sha", "str", False, False)])
 
 # We use make dataclass to dynamically fill the scores from Tasks