diff --git a/optimum/exporters/onnx/model_patcher.py b/optimum/exporters/onnx/model_patcher.py
index 82cec1eeb5e..c90b5baebaf 100644
--- a/optimum/exporters/onnx/model_patcher.py
+++ b/optimum/exporters/onnx/model_patcher.py
@@ -16,7 +16,7 @@
 import functools
 import inspect
 import types
-from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Union
+from typing import TYPE_CHECKING, Any, Callable, Dict, Optional, Union
 
 from transformers.models.speecht5.modeling_speecht5 import SpeechT5EncoderWithSpeechPrenet
 from transformers.utils import is_torch_available
@@ -36,18 +36,6 @@
 logger = logging.get_logger(__name__)
 
 
-def get_argument(argument_name: str, args: List[Any], kwargs: Dict[str, Any], forward_signature):
-    """
-    Get the argument argument_name from the args and kwargs according to the signature forward_signature.
-    """
-    args = list(args)
-    if argument_name in forward_signature.parameters:
-        argument_index = list(forward_signature.parameters.keys()).index(argument_name)
-        return args[argument_index]
-    else:
-        return kwargs[argument_name]
-
-
 def override_arguments(args, kwargs, forward_signature, model_kwargs: Dict[str, Any]):
     """
     Override the args and kwargs with the argument values from model_kwargs, following the signature forward_signature corresponding to args and kwargs.
diff --git a/optimum/exporters/tasks.py b/optimum/exporters/tasks.py
index baf163b1691..a7b2d28facd 100644
--- a/optimum/exporters/tasks.py
+++ b/optimum/exporters/tasks.py
@@ -1400,7 +1400,7 @@ def _infer_task_from_model_name_or_path(
                 pipeline_tag = getattr(model_info, "pipeline_tag", None)
                 # conversational is not a supported task per se, just an alias that may map to
                 # text-generaton or text2text-generation.
-                if pipeline_tag is not None and pipeline_tag not in ["conversational"]:
+                if pipeline_tag is not None and pipeline_tag != "conversational":
                     inferred_task_name = TasksManager.map_from_synonym(model_info.pipeline_tag)
                 else:
                     transformers_info = model_info.transformersInfo