This shows us what the token_type_ids are for: they indicate to the model which part of
the inputs correspond to the first sentence and which part corresponds to the second sentence. Note that
token_type_ids are not required or handled by all models. By default, a tokenizer will only return the inputs that
its associated model expects. You can force the return (or the non-return) of any of those special arguments by using
return_input_ids or return_token_type_ids.
If we decode the token ids we obtained, we will see that the special tokens have been properly added.
```py
tokenizer.decode(encoded_input["input_ids"])
"[CLS] How old are you? [SEP] I'm 6 years old [SEP]"
```
If you have a list of pairs of sequences you want to process, you should feed them as two lists to your tokenizer: the
list of first sentences and the list of second sentences:
