Question Answering with transformers
Answer questions from a context with a Hugging Face question-answering pipeline.
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Updated
A few lines of Python that load a Hugging Face question-answering pipeline and extract an answer from a context window. The script is below.
qa.py
python
from transformers import pipeline
class QuestionAnswering:
def __init__(self, context: str):
model_name = 'Nadav/bert-base-french-europeana-cased-squad-fr'
model_name = 'etalab-ia/camembert-base-squadFR-fquad-piaf'
self._model = pipeline('question-answering', model=model_name, tokenizer=model_name)
self._context = context
def ask(self, question: str, threshold: float = 0.2):
answer = self._model(question = question, context = self._context)
return answer['answer'] if answer['score'] > threshold and answer['answer'] else NoneSomething wrong or want to discuss this article?
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