[tokenizers] Updates data processors, docstring, examples and model cards to the new API (#5308)

* remove references to old API in docstring - update data processors

* style

* fix tests - better type checking error messages

* better type checking

* include awesome fix by @LysandreJik for #5310

* updated doc and examples

src/transformers/file_utils.py

@@ -278,7 +278,7 @@ PT_MULTIPLE_CHOICE_SAMPLE = r"""
         >>> choice1 = "It is eaten while held in the hand."
         >>> labels = torch.tensor(0).unsqueeze(0)  # choice0 is correct (according to Wikipedia ;)), batch size 1
 
-        >>> encoding = tokenizer([[prompt, prompt], [choice0, choice1]], return_tensors='pt', pad_to_max_length=True)
+        >>> encoding = tokenizer([[prompt, prompt], [choice0, choice1]], return_tensors='pt', padding=True)
         >>> outputs = model(**{{k: v.unsqueeze(0) for k,v in encoding.items()}}, labels=labels)  # batch size is 1
 
         >>> # the linear classifier still needs to be trained
@@ -391,7 +391,7 @@ TF_MULTIPLE_CHOICE_SAMPLE = r"""
         >>> choice0 = "It is eaten with a fork and a knife."
         >>> choice1 = "It is eaten while held in the hand."
 
-        >>> encoding = tokenizer([[prompt, prompt], [choice0, choice1]], return_tensors='tf', pad_to_max_length=True)
+        >>> encoding = tokenizer([[prompt, prompt], [choice0, choice1]], return_tensors='tf', padding=True)
         >>> inputs = {{k: tf.expand_dims(v, 0) for k, v in encoding.items()}}
         >>> outputs = model(inputs)  # batch size is 1