from transformers import pipeline
question_answerer = pipeline("question-answering", model='distilbert-base-cased-distilled-squad')

context = r"""
Extractive Question Answering is the task of extracting an answer
from a text given a question. An example of a question answering
dataset is the SQuAD dataset, which is entirely based on that task. If
you would like to fine-tune a model on a SQuAD task, you may leverage
the examples/pytorch/question-answering/run_squad.py script.
"""

result = question_answerer(question="What is a good example of a question answering dataset?",     context=context)
print(f"Answer: '{result['answer']}', score: {round(result['score'], 4)}, start: {result['start']}, end: {result['end']}")