diff --git a/onnxslim/utils.py b/onnxslim/utils.py
index 38b22e3..ea14c16 100644
--- a/onnxslim/utils.py
+++ b/onnxslim/utils.py
@@ -166,7 +166,7 @@ def onnxruntime_inference(model: onnx.ModelProto, input_data: dict) -> Dict[str,
     return onnx_output, model
 
 
-def format_model_info(model_name: str, model_info_list: List[Dict], elapsed_time: float = None):
+def format_model_info(model_info_list: List[Dict], elapsed_time: float = None):
     assert model_info_list, "model_info_list must contain more than one model info"
     if not isinstance(model_info_list, (list, tuple)):
         model_info_list = [model_info_list]
@@ -239,9 +239,12 @@ def get_io_info(model_info_list, tag=None):
     return final_op_info
 
 
-def print_model_info_as_table(model_name: str, model_info_list: List[Dict], elapsed_time: float = None):
+def print_model_info_as_table(model_info_list: List[Dict], elapsed_time: float = None):
     """Prints the model information as a formatted table for the given model name and list of model details."""
-    final_op_info = format_model_info(model_name, model_info_list, elapsed_time)
+    if not isinstance(model_info_list, (list, tuple)):
+        model_info_list = [model_info_list]
+    
+    final_op_info = format_model_info(model_info_list, elapsed_time)
     lines = tabulate(
         final_op_info,
         headers=[],
@@ -260,13 +263,11 @@ def print_model_info_as_table(model_name: str, model_info_list: List[Dict], elap
     print(output)
 
 
-def dump_model_info_to_disk(model_name: str, model_info: Dict):
+def dump_model_info_to_disk(model_info: Dict):
     """Writes model information to a CSV file for a given model name and dictionary of model info."""
     import csv
-    import os
 
-    filename_without_extension, _ = os.path.splitext(os.path.basename(model_name))
-    csv_file_path = f"{filename_without_extension}_model_info.csv"
+    csv_file_path = f"{model_info.tag}_model_info.csv"
     with open(csv_file_path, "a", newline="") as csvfile:  # Use 'a' for append mode
         fieldnames = ["NodeName", "OpType", "OutputDtype", "OutputShape"]
         writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
@@ -422,7 +423,7 @@ def output_maps(self):
         return self.output_dict
 
 
-def summarize_model(model: Union[str, onnx.ModelProto], tag=None) -> Dict:
+def summarize_model(model: Union[str, onnx.ModelProto], tag="OnnxModel") -> Dict:
     """Generates a summary of the ONNX model, including model size, operations, and tensor shapes."""
     logger.debug("Start summarizing model.")
     model_info = ModelInfo(model, tag)
diff --git a/tests/test_modelzoo.py b/tests/test_modelzoo.py
index 858b604..3b6cd32 100644
--- a/tests/test_modelzoo.py
+++ b/tests/test_modelzoo.py
@@ -49,16 +49,16 @@ def test_tiny_en_decoder(self, request):
     def test_transformer_encoder(self, request):
         name = request.node.originalname[len("test_") :]
         filename = f"{MODELZOO_PATH}/{name}/{name}.onnx"
-        summary = summarize_model(slim(filename))
-        print_model_info_as_table(request.node.name, summary)
+        summary = summarize_model(slim(filename), tag=request.node.name)
+        print_model_info_as_table(summary)
         assert summary.op_type_counts["Mul"] == 57
         assert summary.op_type_counts["Div"] == 53
 
     def test_uiex(self, request):
         name = request.node.originalname[len("test_") :]
         filename = f"{MODELZOO_PATH}/{name}/{name}.onnx"
-        summary = summarize_model(slim(filename))
-        print_model_info_as_table(request.node.name, summary)
+        summary = summarize_model(slim(filename), tag=request.node.name)
+        print_model_info_as_table(summary)
         assert summary.op_type_counts["Range"] == 0
         assert summary.op_type_counts["Floor"] == 0
         assert summary.op_type_counts["Concat"] == 54