 'id': '5733be284776f41900661182',
 'question': 'To whom did the Virgin Mary allegedly appear in 1858 in Lourdes France?',
 'title': 'University_of_Notre_Dame'
}
```
Preprocess
Load the DistilBERT tokenizer with an [AutoTokenizer]:
```python
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("distilbert-base-uncased")
```
There are a few things to be aware of when preprocessing text for question answering:
Some examples in a dataset may have a very long context that exceeds the maximum input length of the model. You
   can deal with this by truncating the context and set truncation="only_second".
Next, you need to map the start and end positions of the answer to the original context. Set
   return_offset_mapping=True to handle this.
With the mapping in hand, you can find the start and end tokens of the answer. Use the sequence_ids method to
