                   [0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], 
                   [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1]], 
'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], 
                   [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], 
                   [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}
```
As we can see, it returns a dictionary where each value is a list of lists of ints.
To double-check what is fed to the model, we can decode each list in input_ids one by one:
```py
for ids in encoded_inputs["input_ids"]:
...     print(tokenizer.decode(ids))
[CLS] Hello I'm a single sentence [SEP] I'm a sentence that goes with the first sentence [SEP]
[CLS] And another sentence [SEP] And I should be encoded with the second sentence [SEP]
