datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
natural_questions
Dataset Card for Natural Questions
Dataset Summary
The NQ corpus contains questions from real users, and it requires QA systems to
read and comprehend an entire Wikipedia article that may or may not contain the
answer to the question. The inclusion of real user questions, and the
requirement that solutions should read an entire page to find the answer, cause
NQ to be a more realistic and challenging task than prior QA datasets.
Supported Tasks and Leaderboards… See the full description on the dataset page: https://huggingface.co/datasets/google-research-datasets/natural_questions.web_questions
Dataset Card for "web_questions"
Dataset Summary
This dataset consists of 6,642 question/answer pairs.
The questions are supposed to be answerable by Freebase, a large knowledge graph.
The questions are mostly centered around a single named entity.
The questions are popular ones asked on the web (at least in 2013).
Supported Tasks and Leaderboards
More Information Needed
Languages
More Information Needed
Dataset Structure
Data… See the full description on the dataset page: https://huggingface.co/datasets/stanfordnlp/web_questions.docvqa-single-page-questions
Dataset Card for DocVQA Dataset
Dataset Summary
DocVQA dataset is a document dataset introduced in Mathew et al. (2021) consisting of 50,000 questions defined on 12,000+ document images.
Please visit the challenge page (https://rrc.cvc.uab.es/?ch=17) and paper (https://arxiv.org/abs/2007.00398) for further information.
Usage
This dataset can be used with current releases of Hugging Face datasets library.
Here is an example using a custom collator to bundle… See the full description on the dataset page: https://huggingface.co/datasets/pixparse/docvqa-single-page-questions.NLU-Question-Answering
SEA Question Answering
SEA Question Answering evaluates a model's ability to predict a contiguous span of characters that answers the question about a given passage. It is sampled from TyDi QA-GoldP for Indonesian, IndicQA for Tamil, and XQuaD for Thai and Vietnamese.
Supported Tasks and Leaderboards
SEA Question Answering is designed for evaluating chat or instruction-tuned large language models (LLMs). It is part of the SEA-HELM leaderboard from AI Singapore.… See the full description on the dataset page: https://huggingface.co/datasets/aisingapore/NLU-Question-Answering.medical-question-answering-datasetsTraditional-Chinese-Medicine-Multiple_choice_question
Discription
This dataset is sourced from the website of the Ministry of Examination, R.O.C (Taiwan) and contains past exam questions from the national Traditional Chinese Medicine examinations in Taiwan. The exam comprises six subjects. This dataset specifically includes questions from two subjects, including the History of Traditional Chinese Medicine, Basic Theories of Traditional Chinese Medicine, Neijing, Nanjing, Traditional Chinese Medicine Prescription Studies, and… See the full description on the dataset page: https://huggingface.co/datasets/Liavan/Traditional-Chinese-Medicine-Multiple_choice_question.natural_questions
Dataset Card for Natural Questions
Dataset Summary
The NQ corpus contains questions from real users, and it requires QA systems to
read and comprehend an entire Wikipedia article that may or may not contain the
answer to the question. The inclusion of real user questions, and the
requirement that solutions should read an entire page to find the answer, cause
NQ to be a more realistic and challenging task than prior QA datasets.
Supported Tasks and… See the full description on the dataset page: https://huggingface.co/datasets/shehabsalaheldin/natural_questions.jee-main-questions
JEE Main — Question Bank
A structured dataset of JEE Main examination questions with full metadata,
worked solutions, and diagrams. Built for education, ML training, and
question-generation use cases.
Subsets:
Chemistry — 738 questions from 28 papers
Physics — 768 questions from 28 papers
Mathematics — 801 questions from 28 papers
Over 2,300 questions across the three core JEE subjects.
Structure
Organised into subsets by subject and splits (train / test):… See the full description on the dataset page: https://huggingface.co/datasets/eQOURSE/jee-main-questions.rakuda-questions
Rakuda - Questions for Japanese models
Repository: https://github.com/yuzu-ai/japanese-llm-ranking
This is a set of 40 questions in Japanese about Japanese-specific topics designed to evaluate the capabilities of AI Assistants in Japanese.
The questions are evenly distributed between four categories: history, society, government, and geography.
Questions in the first three categories are open-ended, while the geography questions are more specific.
Answers to these questions can be… See the full description on the dataset page: https://huggingface.co/datasets/yuzuai/rakuda-questions.text-sft-questions-answers-only
text-sft: Questions and Answers
This dataset consists of question-and-answer pairs generated from short excerpts drawn from Wikipedia, Cosmopedia, and FineWeb-Edu. It is an adapted version of agentlans/text-sft.
Overview
The dataset provides compact examples of English question-and-answer relationships that can help models learn linguistic patterns, syntactic structures, and semantic associations between questions and their corresponding answers.
Intended Use… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/text-sft-questions-answers-only.simple_questions_v2SimpleQuestions is a dataset for simple QA, which consists
of a total of 108,442 questions written in natural language by human
English-speaking annotators each paired with a corresponding fact,
formatted as (subject, relationship, object), that provides the answer
but also a complete explanation. Fast have been extracted from the
Knowledge Base Freebase (freebase.com). We randomly shuffle these
questions and use 70% of them (75910) as training set, 10% as
validation set (10845), and the remaining 20% as test set.jee-main-questions
JEE Main — Question Bank
A structured dataset of JEE Main examination questions with full metadata,
worked solutions, and diagrams. Built for education, ML training, and
question-generation use cases.
Subsets:
Chemistry — 738 questions from 28 papers
Physics — 768 questions from 28 papers
Mathematics — 801 questions from 28 papers
Over 2,300 questions across the three core JEE subjects.
Structure
Organised into subsets by subject and splits (train / test):… See the full description on the dataset page: https://huggingface.co/datasets/soughed/jee-main-questions.natural_questions_cleanresearchy_questions
Introduction
Researchy Questions is a set of about 100k Bing queries that users spent the most effort on. After a labor-intensive filtering funnel from billions of queries, these "needles in the haystack" are non-factoid, multi-perspective questions that probably require a lot of sub-questions and research in order to answer adequetly. These questions are shown to be harder than other open domain QA datasets like Natural Questions.
The train dataset has about 90k samples.… See the full description on the dataset page: https://huggingface.co/datasets/corbyrosset/researchy_questions.question-type-and-complexity
Question Type and Complexity (QTC) Dataset
Dataset Overview
The Question Type and Complexity (QTC) dataset is a comprehensive resource for linguistics/NLP research focusing on question classification and linguistic complexity analysis across multiple languages. It contains questions from two distinct sources (TyDi QA and Universal Dependencies v2.15), automatically annotated with question types (polar/content) and a set of linguistic complexity features.
Key Features:
2… See the full description on the dataset page: https://huggingface.co/datasets/rokokot/question-type-and-complexity.Flutter-Code-with-Questions-Dataset-Turkish
Flutter Code with Questions Dataset (Turkish)
📦 Dataset Name: flutter_code_with_questions
Bu veri seti, Flutter framework'ü ile yazılmış kod parçacıkları ve her bir kod parçası için özel olarak üretilmiş detaylı Türkçe soruları içermektedir. Veri seti, kodların eğitim verisi olarak kullanılmasının yanı sıra, LLM (Large Language Model) tabanlı kod anlama ve soru yanıtlama modellerinin geliştirilmesinde kullanılabilir.
📁 Dataset Format
Veri dosyaları CSV… See the full description on the dataset page: https://huggingface.co/datasets/NoirZangetsu/Flutter-Code-with-Questions-Dataset-Turkish.jee-advanced-questions
JEE Advanced — Question Bank
A structured dataset of JEE Advanced examination questions with full
worked solutions and diagrams. JEE Advanced questions are more analytical
than JEE Main — many are subjective, integer, or numerical-answer type with
detailed multi-step solutions.
Subsets (PCM):
Physics — 50 questions
Chemistry — 21 questions
Mathematics — 48 questions
Structure
Organised into subsets by subject and splits (train / test):
mathematics/ physics/… See the full description on the dataset page: https://huggingface.co/datasets/eQOURSE/jee-advanced-questions.Flutter-Code-with-Questions-Dataset-English
🧠 Flutter Code with Questions Dataset (English)
This repository contains a high-quality dataset of Flutter-related code snippets paired with automatically generated English technical questions. The dataset is intended for use in training and fine-tuning language models, coding assistants, and educational systems focused on Flutter development.
📂 Dataset Structure
The dataset is divided into 22 CSV files, each containing 200 entries. Every entry includes:
A… See the full description on the dataset page: https://huggingface.co/datasets/NoirZangetsu/Flutter-Code-with-Questions-Dataset-English.natural-questions-val-lance
Natural Questions — Validation (Lance Format)
A Lance-formatted version of the Natural Questions validation split — 7,830 real Google search queries paired with the full Wikipedia article a human used to answer them, plus 1–5 annotator labels per question. MiniLM question embeddings are stored inline and the dataset ships with pre-built ANN/FTS indices, all available directly from the Hub at hf://datasets/lance-format/natural-questions-val-lance/data. Sourced from… See the full description on the dataset page: https://huggingface.co/datasets/lance-format/natural-questions-val-lance.conv_questionsConvQuestions is the first realistic benchmark for conversational question answering over knowledge graphs.
It contains 11,200 conversations which can be evaluated over Wikidata. The questions feature a variety of complex
question phenomena like comparisons, aggregations, compositionality, and temporal reasoning.natural-questions-slim-short-answer
Natural Questions Slim Short Answer
This is a slim, flattened derived version of
google-research-datasets/natural_questions
for short-answer question answering experiments.
The conversion keeps examples with extractable short answers and removes the
original document HTML, token-level document spans, long answer candidates, and
yes/no-only examples. Each record is a simple question-answer pair. It is
intended for lightweight QA prompting and evaluation, not as a full replacement
for… See the full description on the dataset page: https://huggingface.co/datasets/BOB12311/natural-questions-slim-short-answer.jee-main-questions
JEE Main — Question Bank
A structured dataset of JEE Main examination questions with full metadata,
worked solutions, and diagrams. Built for education, ML training, and
question-generation use cases.
Subsets:
Chemistry — 738 questions from 28 papers
Physics — 768 questions from 28 papers
Mathematics — 801 questions from 28 papers
Over 2,300 questions across the three core JEE subjects.
Structure
Organised into subsets by subject and splits (train / test):… See the full description on the dataset page: https://huggingface.co/datasets/Grass-G/jee-main-questions.quora-question-answer-datasetQuora Question Answer Dataset (Quora-QuAD) contains 56,402 question-answer pairs scraped from Quora.
Usage:
For instructions on fine-tuning a model (Flan-T5) with this dataset, please check out the article: https://www.toughdata.net/blog/post/finetune-flan-t5-question-answer-quora-dataset
cybersecurity-questionaire
Dataset Card for cybersecurity-questionaire
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/MichaelPrimez/cybersecurity-questionaire/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/MichaelPrimez/cybersecurity-questionaire.Question-AnsweringThis is the question answering datasets collected by TextBox, including:
SQuAD (squad)
CoQA (coqa)
Natural Questions (nq)
TriviaQA (tqa)
WebQuestions (webq)
NarrativeQA (nqa)
MS MARCO (marco)
NewsQA (newsqa)
HotpotQA (hotpotqa)
MSQG (msqg)
QuAC (quac).
The detail and leaderboard of each dataset can be found in TextBox page.
forecastbench-single_question
ForecastBench Single Questions
This dataset contains single-ID forecasting questions derived from the ForecastBench project. It includes two configurations:
forecastbench_single_questions_2024-12-08: Contains 429 forecasting questions with resolved real-world outcomes.
forecastbench_single_questions_human_2024-07-21: Contains 473 questions with resolved real-world outcomes, augmented with human forecast probabilities from public and superforecaster groups.
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/Duruo/forecastbench-single_question.Turkish-medical-visual-question-answering-LLaVa-dataset
Türkçe Radyoloji Görüntüleme Veri Seti - data_RAD
data_RAD veri seti, radyoloji görüntüleri üzerinde görsel soru-cevaplama (VQA) araştırmaları yapmak amacıyla Türkçeye çevrilmiş ve LLaVa mimarisiyle uyumlu hale getirilmiştir. Bu veri seti, tıbbi görüntü analizi ve yapay zeka destekli radyoloji uygulamalarını geliştirmek için kullanılabilir.
Veri Seti İçeriği
Toplam Görüntü Sayısı: 316
Veri Yapısı: DatasetDict({ train: Dataset({ features: ['image'], num_rows: 316 }) })
Özellikler:… See the full description on the dataset page: https://huggingface.co/datasets/nezahatkorkmaz/Turkish-medical-visual-question-answering-LLaVa-dataset.granola-entity-questions
GRANOLA Entity Questions Dataset Card
Dataset details
Dataset Name: GRANOLA-EQ (Granularity of Labels Entity Questions)
Paper: Narrowing the Knowledge Evaluation Gap: Open-Domain Question Answering with Multi-Granularity Answers
Abstract: Factual questions typically can be answered correctly at different levels of granularity. For example, both "August 4, 1961" and "1961" are correct answers to the question "When was Barack Obama born?"". Standard question answering (QA)… See the full description on the dataset page: https://huggingface.co/datasets/google/granola-entity-questions.wb-questions
Dataset Card for Wildberries questions
Dataset Summary
This is a dataset of questions and answers scraped from product pages from the Russian marketplace Wildberries. Dataset contains all questions and answers, as well as all metadata from the API. However, the "productName" field may be empty in some cases because the API does not return the name for old products.
Languages
The dataset is mostly in Russian, but there may be other languages present.… See the full description on the dataset page: https://huggingface.co/datasets/nyuuzyou/wb-questions.stackoverflow-kubernetes-questionsThe purpose of this dataset is to provide the opportunity to perform any training, fine-tuning, etc. for any Language Model. In the 'data' folder, you will find the dataset in Parquet format, which is one of the formats used for these processes.
In case it may be useful for other purposes, I have also included the dataset in CSV format.
All data in this dataset were retrieved from the Stack Exchange network using the Stack Exchange Data explorer tool… See the full description on the dataset page: https://huggingface.co/datasets/mcipriano/stackoverflow-kubernetes-questions.