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Dataset: quail 🏷
Update on GitHub

How to load this dataset directly with the πŸ€—/datasets library:

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from datasets import load_dataset dataset = load_dataset("quail")


QuAIL is a reading comprehension dataset. QuAIL contains 15K multi-choice questions in texts 300-350 tokens long 4 domains (news, user stories, fiction, blogs).QuAIL is balanced and annotated for question types.\


  author    = {Anna Rogers and
               Olga Kovaleva and
               Matthew Downey and
               Anna Rumshisky},
  title     = {Getting Closer to {AI} Complete Question Answering: {A} Set of Prerequisite
               Real Tasks},
  booktitle = {The Thirty-Fourth {AAAI} Conference on Artificial Intelligence, {AAAI}
               2020, The Thirty-Second Innovative Applications of Artificial Intelligence
               Conference, {IAAI} 2020, The Tenth {AAAI} Symposium on Educational
               Advances in Artificial Intelligence, {EAAI} 2020, New York, NY, USA,
               February 7-12, 2020},
  pages     = {8722--8731},
  publisher = {{AAAI} Press},
  year      = {2020},
  url       = {},
  timestamp = {Thu, 04 Jun 2020 13:18:48 +0200},
  biburl    = {},
  bibsource = {dblp computer science bibliography,}

Models trained or fine-tuned on quail

None yet. Start fine-tuning now =)