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nlpconnect/deberta-v3-xsmall-squad2
deberta-v3-xsmall-squad2 is a question answering model from nlpconnect. Use it when the input is a question plus a passage. It is set up for transformers. The card lists the license as apache-2.0.
Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or…
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From the Hugging Face model README
Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable.
SQuAD2.0 combines the 100,000 questions in SQuAD1.1 with over 50,000 unanswerable questions written adversarially by crowdworkers to look similar to answerable ones. To do well on SQuAD2.0, systems must not only answer questions when possible, but also determine when no answer is supported by the paragraph and abstain from answering.
from transformers import pipeline
qa = pipeline("question-answering", model="nlpconnect/deberta-v3-xsmall-squad2")
result = qa(context="My name is Sarah and I live in London", question="Where do I live?")
squad_v2 = {'exact': 79.392,
'f1': 82.674}
squad = {'exact': 84.925,
'f1': 91.620}