Clarify return_tensor and return_text parameters (#20662)

* clarify docstring

* make style

src/transformers/pipelines/text_generation.py

@@ -170,11 +170,12 @@ class TextGenerationPipeline(Pipeline):
             args (`str` or `List[str]`):
                 One or several prompts (or one list of prompts) to complete.
             return_tensors (`bool`, *optional*, defaults to `False`):
-                Whether or not to include the tensors of predictions (as token indices) in the outputs.
+                Whether or not to return the tensors of predictions (as token indices) in the outputs. If set to
+                `True`, the decoded text is not returned.
             return_text (`bool`, *optional*, defaults to `True`):
-                Whether or not to include the decoded texts in the outputs.
+                Whether or not to return the decoded texts in the outputs.
             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
+                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`):
                 Whether or not to clean up the potential extra spaces in the text output.
@@ -195,7 +196,8 @@ class TextGenerationPipeline(Pipeline):
                 corresponding to your framework [here](./model#generative-models)).
 
         Return:
-            A list or a list of list of `dict`: Each result comes as a dictionary with the following keys:
+            A list or a list of list of `dict`: Returns one of the following dictionaries (cannot return a combination
+            of both `generated_text` and `generated_token_ids`):
 
             - **generated_text** (`str`, present when `return_text=True`) -- The generated text.
             - **generated_token_ids** (`torch.Tensor` or `tf.Tensor`, present when `return_tensors=True`) -- The token