Fixing NER pipeline for list inputs. (#10184)

Fixes #10168

src/transformers/pipelines/token_classification.py

@@ -28,11 +28,14 @@ class TokenClassificationArgumentHandler(ArgumentHandler):
     Handles arguments for token classification.
     """
 
-    def __call__(self, *args, **kwargs):
+    def __call__(self, inputs: Union[str, List[str]], **kwargs):
 
-        if args is not None and len(args) > 0:
-            inputs = list(args)
+        if inputs is not None and isinstance(inputs, (list, tuple)) and len(inputs) > 0:
+            inputs = list(inputs)
             batch_size = len(inputs)
+        elif isinstance(inputs, str):
+            inputs = [inputs]
+            batch_size = 1
         else:
             raise ValueError("At least one input is required.")
 
@@ -137,11 +140,11 @@ class TokenClassificationPipeline(Pipeline):
               Only exists if the offsets are available within the tokenizer
         """
 
-        inputs, offset_mappings = self._args_parser(inputs, **kwargs)
+        _inputs, offset_mappings = self._args_parser(inputs, **kwargs)
 
         answers = []
 
-        for i, sentence in enumerate(inputs):
+        for i, sentence in enumerate(_inputs):
 
             # Manage correct placement of the tensors
             with self.device_placement():