 'attention_mask': tf.Tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1],
                           [1, 1, 1, 1, 1, 0, 0, 0, 0],
                           [1, 1, 1, 1, 1, 1, 1, 1, 0]])}
```
It returns a dictionary with string keys and tensor values. We can now see what the attention_mask is all about: it points out which tokens the model should pay attention to and which ones
it should not (because they represent padding in this case).
Note that if your model does not have a maximum length associated to it, the command above will throw a warning. You
can safely ignore it. You can also pass verbose=False to stop the tokenizer from throwing those kinds of warnings.
Preprocessing pairs of sentences
Sometimes you need to feed a pair of sentences to your model. For instance, if you want to classify if two sentences in
