a pair are similar, or for question-answering models, which take a context and a question. For BERT models, the input
is then represented like this: [CLS] Sequence A [SEP] Sequence B [SEP]
You can encode a pair of sentences in the format expected by your model by supplying the two sentences as two arguments
(not a list since a list of two sentences will be interpreted as a batch of two single sentences, as we saw before).
This will once again return a dict string to list of ints:
```py
encoded_input = tokenizer("How old are you?", "I'm 6 years old")
print(encoded_input)
{'input_ids': [101, 1731, 1385, 1132, 1128, 136, 102, 146, 112, 182, 127, 1201, 1385, 102], 
 'token_type_ids': [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1], 
 'attention_mask': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]}
```
