Fix a typo

src/transformers/pipelines/conversational.py

@@ -272,7 +272,7 @@ def __call__(self, conversations: Union[List[Dict], Conversation, List[Conversat
                 Conversation to generate responses for. Inputs can also be passed as a list of dictionaries with `role`
                 and `content` keys - in this case, they will be converted to `Conversation` objects automatically.
                 Multiple conversations in either format may be passed as a list.
-            clean_up_tokenization_spaces (`bool`, *optional*, defaults to `False`):
+            clean_up_tokenization_spaces (`bool`, *optional*, defaults to `True`):
                 Whether or not to clean up the potential extra spaces in the text output.
             generate_kwargs:
                 Additional keyword arguments to pass along to the generate method of the model (see the generate method

src/transformers/pipelines/text_generation.py

@@ -204,7 +204,7 @@ def __call__(self, text_inputs, **kwargs):
             return_full_text (`bool`, *optional*, defaults to `True`):
                 If set to `False` only added text is returned, otherwise the full text is returned. Only meaningful if
                 *return_text* is set to True.
-            clean_up_tokenization_spaces (`bool`, *optional*, defaults to `False`):
+            clean_up_tokenization_spaces (`bool`, *optional*, defaults to `True`):
                 Whether or not to clean up the potential extra spaces in the text output.
             prefix (`str`, *optional*):
                 Prefix added to prompt.