datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
squad
Dataset Card for SQuAD
Dataset Summary
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.
SQuAD 1.1 contains 100,000+ question-answer pairs on 500+ articles.
Supported Tasks and Leaderboards
Question… See the full description on the dataset page: https://huggingface.co/datasets/rajpurkar/squad.squad_v2
Dataset Card for SQuAD 2.0
Dataset Summary
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.
SQuAD 2.0 combines the 100,000 questions in SQuAD1.1 with over 50,000 unanswerable questions written adversarially by crowdworkers… See the full description on the dataset page: https://huggingface.co/datasets/rajpurkar/squad_v2.qa_squadshifts_synthetic_randomTBA
custom_squadStanford 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.SQuADDS_Layouts
SQuADDS Layouts - versioned GDS artifacts for superconducting quantum hardware
SQuADDS Layouts is the geometry-artifact companion to
SQuADDS_DB, the
Superconducting Qubit And Device Design and Simulation Database. It provides
checksum-verified GDS files, stable geometry identities, and machine-readable
geometry metadata so a simulation result can be traced to the exact layout
that produced it.
Homepage: https://lfl-lab.github.io/SQuADDS/
Repository:… See the full description on the dataset page: https://huggingface.co/datasets/SQuADDS/SQuADDS_Layouts.based-squadPlease consider citing the following if you use this task in your work:
@inproceedings{Rajpurkar2018SQuAD2,
title={Know What You Don't Know: Unanswerable Questions for SQuAD},
author={Pranav Rajpurkar and Jian Zhang and Percy Liang},
booktitle={ACL 2018},
year={2018}
}
@article{arora2024simple,
title={Simple linear attention language models balance the recall-throughput tradeoff},
author={Arora, Simran and Eyuboglu, Sabri and Zhang, Michael and Timalsina, Aman and Alberti, Silas… See the full description on the dataset page: https://huggingface.co/datasets/hazyresearch/based-squad.qa_squadshifts_synthetic
Dataset Card for "lmqg/qa_squadshifts_synthetic"
Dataset Summary
This is a synthetic QA dataset generated with fine-tuned QG models over lmqg/qa_squadshifts, made for question-answering based evaluation (QAE) for question generation model proposed by Zhang and Bansal, 2019.
The test split is the original validation set of lmqg/qa_squadshifts, where the model should be evaluate on.
Supported Tasks and Leaderboards
question-answering
Languages… See the full description on the dataset page: https://huggingface.co/datasets/lmqg/qa_squadshifts_synthetic.squad-gen2mcloki-expLLM
Dataset Card for Loki Honeypot Interaction Dataset
Dataset Summary
This dataset contains interaction logs from the Loki project, a research initiative focused on creating scalable, LLM-powered honeypots. The data captures requests made to three different honeypot experiments (Exp0, Exp1, and Exp2), each with a unique architecture and purpose. The primary goal of this dataset is to provide researchers and security professionals with real-world examples of… See the full description on the dataset page: https://huggingface.co/datasets/squad-rnd/loki-expLLM.SQuADDS_DB
SQuADDS_DB - a Superconducting Qubit And Device Design and Simulation Database
The SQuADDS (Superconducting Qubit And Device Design and Simulation) Database Project is an open-source resource aimed at advancing research in superconducting quantum device designs. It provides a robust workflow for generating and simulating superconducting quantum device designs, facilitating the accurate prediction of Hamiltonian parameters across a wide range of design geometries.… See the full description on the dataset page: https://huggingface.co/datasets/SQuADDS/SQuADDS_DB.squadsquad
Dataset Card for SQuAD
This dataset is a collection of question-answer pairs from the SQuAD dataset. See SQuAD for additional information.
This dataset can be used directly with Sentence Transformers to train embedding models.
Dataset Subsets
pair subset
Columns: "question", "answer"
Column types: str, str
Examples:{
'question': 'To whom did the Virgin Mary allegedly appear in 1858 in Lourdes France?',
'answer': 'Architecturally, the school has a Catholic… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/squad.qg_squad[SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) evaluation set for the question generation (QG) models. The split
of test and development set follows the ["Neural Question Generation"](https://arxiv.org/abs/1705.00106) work and is
compatible with the [leader board](https://paperswithcode.com/sota/question-generation-on-squad11).squadshifts
Dataset Card for "squadshifts"
Dataset Summary
SquadShifts consists of four new test sets for the Stanford Question Answering Dataset (SQuAD) from four different domains: Wikipedia articles, New York Times articles, Reddit comments, and Amazon product reviews. Each dataset was generated using the same data generating pipeline, Amazon Mechanical Turk interface, and data cleaning code as the original SQuAD v1.1 dataset. The "new-wikipedia" dataset measures overfitting on… See the full description on the dataset page: https://huggingface.co/datasets/ludwigschmidt/squadshifts.squad_v2squad_kor_v1
Dataset Card for KorQuAD v1.0
Dataset Summary
KorQuAD 1.0 is a large-scale question-and-answer dataset constructed for Korean machine reading comprehension, and investigate the dataset to understand the distribution of answers and the types of reasoning required to answer the question. This dataset benchmarks the data generating process of SQuAD v1.0 to meet the standard.
Supported Tasks and Leaderboards
question-answering
Languages
Korean… See the full description on the dataset page: https://huggingface.co/datasets/KorQuAD/squad_kor_v1.squad_mcSQuAD: 100,000+ Questions for Machine Comprehension of Text
NOTE: this is the reformulated multiple choice version of the SQuAD task, with downsampling.
TriviaQA-in-SQuAD-format
Dataset Card for "TriviaQA-in-SQuAD-format"
More Information needed
spoken-squad-t2asquad-conteb-train
ConTEB - SQuAD (training)
This dataset is part of ConTEB (Context-aware Text Embedding Benchmark), designed for evaluating contextual embedding model capabilities. It stems from the widely used SQuAD dataset.
Dataset Summary
SQuAD is an extractive QA dataset with questions associated to passages and annotated answer spans, that allow us to chunk individual passages into shorter sequences while preserving the original annotation. To build the corpus, we start from the… See the full description on the dataset page: https://huggingface.co/datasets/illuin-conteb/squad-conteb-train.qg_squadshifts[SQuAD Shifts](https://modestyachts.github.io/squadshifts-website/index.html) dataset for question generation (QG) task.squad-cisquad_v2 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.pixel_squad
Dataset Card for "pixel_squad"
More Information needed
squad-conteb-eval
ConTEB - SQuAD (evaluation)
This dataset is part of ConTEB (Context-aware Text Embedding Benchmark), designed for evaluating contextual embedding model capabilities. It stems from the widely used SQuAD dataset.
Dataset Summary
SQuAD is an extractive QA dataset with questions associated to passages and annotated answer spans, that allow us to chunk individual passages into shorter sequences while preserving the original annotation. To build the corpus, we start from the… See the full description on the dataset page: https://huggingface.co/datasets/illuin-conteb/squad-conteb-eval.iapp_wiki_qa_squad
iapp_wiki_qa_squad
Extractive question answering over Thai Wikipedia articles, in SQuAD format.
7,242 questions across 1,912 articles, annotated by people iApp hired for the purpose.
from datasets import load_dataset
dataset = load_dataset("iapp/iapp_wiki_qa_squad")
This works again as of the August 2026 revision. Until then it did not. The
repository carried a loading script and no data, and datasets dropped script support
at v3, so load_dataset failed and every… See the full description on the dataset page: https://huggingface.co/datasets/iapp/iapp_wiki_qa_squad.squad_kor_v1squad_adversarialHere are two different adversaries, each of which uses a different procedure to pick the sentence it adds to the paragraph:
AddSent: Generates up to five candidate adversarial sentences that don't answer the question, but have a lot of words in common with the question. Picks the one that most confuses the model.
AddOneSent: Similar to AddSent, but just picks one of the candidate sentences at random. This adversary is does not query the model in any way.spoken_squad_testThis dataset is licensed under the terms of the CC-BY-SA-4.0 license.
https://github.com/Chia-Hsuan-Lee/Spoken-SQuAD/blob/master/LICENSE.md
Author: @michaellee886
@article{li2018spoken,
title={Spoken SQuAD: A study of mitigating the impact of speech recognition errors on listening comprehension},
author={Li, Chia-Hsuan and Wu, Szu-Lin and Liu, Chi-Liang and Lee, Hung-yi},
journal={arXiv preprint arXiv:1804.00320},
year={2018}
}
@article{wang2024audiobench,
title={AudioBench: A… See the full description on the dataset page: https://huggingface.co/datasets/AudioLLMs/spoken_squad_test.squad_it
Dataset Card for "squad_it"
Dataset Summary
SQuAD-it is derived from the SQuAD dataset and it is obtained through semi-automatic translation of the SQuAD dataset
into Italian. It represents a large-scale dataset for open question answering processes on factoid questions in Italian.
The dataset contains more than 60,000 question/answer pairs derived from the original English dataset. The dataset is
split into training and test sets to support the replicability of the… See the full description on the dataset page: https://huggingface.co/datasets/crux82/squad_it.