datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
medical-qa-datasets
all-processed dataset is a concatenation of of medical-meadow-* and chatdoctor_healthcaremagic datasets
The Chat Doctor term is replaced by the chatbot term in the chatdoctor_healthcaremagic dataset
Similar to the literature the medical_meadow_cord19 dataset is subsampled to 50,000 samples
truthful-qa-* is a benchmark dataset for evaluating the truthfulness of models in text generation, which is used in Llama 2 paper. Within this dataset, there are 55 and 16 questions related to Health and… See the full description on the dataset page: https://huggingface.co/datasets/lavita/medical-qa-datasets.Knowledge-QA-SingleTurn-Dataset
Knowledge QA Single-turn Dataset（知識質問データセット・シングルターン）
概要
本データセットは、Aratako/Synthetic-JP-Conversations-Magpie-Nemotron-4-10k から質問を抽出し、DeepSeek V3.2で整形、Kimi K2.5で回答を生成した シングルターンの知識質問応答データセット です。Reasoning有効化により思考過程も最終データに含まれ、質問の難易度に応じてReasoning effortが動的に切り替わります。
生成にはSDG-LOOMという合成データ生成パイプラインを用いました。（sdg-loom）
データの説明
項目
内容
件数
約7,000件
形式
JSONL（1行1JSON）
言語
日本語
ターン数
1ターン（質問1 + 回答1）
ソースデータセット… See the full description on the dataset page: https://huggingface.co/datasets/DataPilot/Knowledge-QA-SingleTurn-Dataset.STRIDE-QA-Dataset
STRIDE-QA Dataset
📦 Dataset
STRIDE-QA is a large-scale visual question answering (VQA) dataset for physically grounded spatiotemporal reasoning in autonomous driving. Constructed from 100 hours of multi-sensor driving data in Tokyo, it offers 16 M QA pairs over 270 K frames with dense annotations including 3D bounding boxes, segmentation masks, and multi-object tracks.
Category
Description
Object-centric Spatial QA
Spatial relations between two… See the full description on the dataset page: https://huggingface.co/datasets/turing-motors/STRIDE-QA-Dataset.egms-qa-dataset
EGMS-QA Dataset
Prepared EGMS displacement tiles, encoder tokens, task labels, reference tables,
and natural-language QA records for 10,000 overlapping 7 km tiles. This card
describes the available data, file formats, and download options.
Data access
Data needed
Files to download
Details
Published QA records
train.jsonl, validation.jsonl, test.jsonl
QA loading example
Encoder inputs
Source tiles, metadata
Encoder data
Translator inputs
Token cache… See the full description on the dataset page: https://huggingface.co/datasets/risenyard/egms-qa-dataset.qa_zre
Dataset Card for QaZre
Dataset Summary
A dataset reducing relation extraction to simple reading comprehension questions
Supported Tasks and Leaderboards
More Information Needed
Languages
More Information Needed
Dataset Structure
Data Instances
default
Size of downloaded dataset files: 516.06 MB
Size of the generated dataset: 2.09 GB
Total amount of disk used: 2.60 GB
An example of 'validation' looks as follows.
{… See the full description on the dataset page: https://huggingface.co/datasets/community-datasets/qa_zre.proto_qa
Dataset Card for [Dataset Name]
Dataset Summary
This dataset is for studying computational models trained to reason about prototypical situations. It is anticipated that still would not lead to usage in a downstream task, but as a way of studying the knowledge (and biases) of prototypical situations already contained in pre-trained models. The data it is partially based on (Family Feud).
Using deterministic filtering a sampling from a larger set of all transcriptions was… See the full description on the dataset page: https://huggingface.co/datasets/community-datasets/proto_qa.annual-report-qa-datasetatpl_qa_dataset
Q&A ATPL Dataset for Aviation Industry
This dataset contains a collection of questions and answers related to the Airline Transport Pilot License (ATPL) exam. It is designed to assist in the preparation for the ATPL exams and can be used for fine-tuning large language models (LLMs) for the aviation industry.
Dataset Details
Name: JAA ATPL Question Bank
Format: Excel (converted to Hugging Face Dataset)
Content: Questions, multiple-choice answers, correct answers, and… See the full description on the dataset page: https://huggingface.co/datasets/tolgadev/atpl_qa_dataset.multimodal_qa_dataset_v1logical-reasoning-qa-dataset
Dataset Card for "logical-reasoning-qa-dataset"
More Information needed
disfl_qa
Dataset Card for DISFL-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering
Dataset Summary
Disfl-QA is a targeted dataset for contextual disfluencies in an information seeking setting, namely question answering over Wikipedia passages. Disfl-QA builds upon the SQuAD-v2 (Rajpurkar et al., 2018) dataset, where each question in the dev set is annotated to add a contextual disfluency using the paragraph as a source of distractors.
The final dataset… See the full description on the dataset page: https://huggingface.co/datasets/google-research-datasets/disfl_qa.FinQA_TAT-QA_financial_finetuning_dataset
Dataset Summary
This dataset provides a unified, flattened context / question / answer format for
question answering over financial documents that combine tabular and textual data. It is
built to support training and evaluating models on numerical and discrete reasoning
tasks in the finance domain, drawing on the structure and style of established
finance-QA benchmarks such as TAT-QA and FinQA.
Each example pairs a passage of financial context (derived from a table and/or… See the full description on the dataset page: https://huggingface.co/datasets/hellotayssir/FinQA_TAT-QA_financial_finetuning_dataset.ft-llm-2026-qa-dataset
FT-LLM 2026 QA Dataset
A Japanese visual-question-answering dataset used for Stage 1-2 visual instruction tuning of the COMPASS Vision-Language Model. Each sample contains a document or natural image together with one or more Japanese question–answer pairs, and is designed to give the VLM its instruction-following and VQA capabilities. Images are embedded in the dataset, so no external downloads are required.
Part of the Compass collection.
License
Released under the… See the full description on the dataset page: https://huggingface.co/datasets/Yana/ft-llm-2026-qa-dataset.mnemonic-qa-datasethr-policies-qa-dataset
📚 HR Policies Q&A Dataset
🔎 Overview
This dataset provides multi-turn Q&A conversations on HR policies and compliance, formatted with system, user, and assistant roles.It is designed for:
🤖 LLM fine-tuning
💬 HR & compliance chatbots
🏢 Enterprise policy automation
By covering real-world HR scenarios — such as policy reviews, compliance processes, and employee communication — this dataset helps train assistants that can:
✅ Clarify company policies✅ Ensure… See the full description on the dataset page: https://huggingface.co/datasets/strova-ai/hr-policies-qa-dataset.pao-instruction-qa-conversation-datasetPa'O Instruction, QA & Conversation Dataset
An open and community-driven dataset for the Pa'O ("blk") language, developed through the RYPAK Ecosystem, SuccessImprove (SI), and Pa'O Digital Hub.
The dataset is designed to support natural language processing (NLP), large language models (LLMs), conversational dialogue, instruction following, language technology research, and digital preservation of the Pa'O language.
The project focuses on building a free, open, reusable, and continuously… See the full description on the dataset page: https://huggingface.co/datasets/paodigitalhub/pao-instruction-qa-conversation-dataset.VIGIA-QA-datasetko_QA_datasetmaywell/korean_textbooks 의 dataset을 Q&A 형식으로 재구성한 dataset입니다.
medical-qa-datasets
all-processed dataset is a concatenation of of medical-meadow-* and chatdoctor_healthcaremagic datasets
The Chat Doctor term is replaced by the chatbot term in the chatdoctor_healthcaremagic dataset
Similar to the literature the medical_meadow_cord19 dataset is subsampled to 50,000 samples
truthful-qa-* is a benchmark dataset for evaluating the truthfulness of models in text generation, which is used in Llama 2 paper. Within this dataset, there are 55 and 16 questions related to Health and… See the full description on the dataset page: https://huggingface.co/datasets/ZuoXiaojia/medical-qa-datasets.multimodal_qa_dataset_v4_trainbangladesh-legal-qa-dataset
Bangladesh Legal QA Dataset: Bangla-English Law and Fine-Tuning
The Bangladesh Legal QA Dataset is a bilingual Bangla-English dataset for
Bangladesh law question answering, legal NLP, LLM fine-tuning, instruction
tuning, and retrieval-augmented generation (RAG). It provides 2,165
context-grounded legal QA records, direct-answer and IRAC chat-format training
data, and structured statutory text from six Bangladesh Acts and three
schedules.
This is the 2,165-record paper-aligned… See the full description on the dataset page: https://huggingface.co/datasets/momahadi/bangladesh-legal-qa-dataset.multimodal_qa_dataset_v3_trainamateur-radio-qa-dataset
📻 Amateur Radio & Electronics QA Dataset (SFT / DPO / Chat)
This dataset is a comprehensive, production-grade bilingual (English and Turkish) corpus dedicated to Amateur Radio (Ham Radio), RF Engineering, Software Defined Radio (SDR), Signal Processing (DSP), Antennas, and Telecommunications Electronics.
Generated and verified using the Elektor Universal Dataset Generator Pipeline (Phase 1-4) with strict LLM-as-a-Judge 5D quality filtering and Google LangExtract… See the full description on the dataset page: https://huggingface.co/datasets/onkanat/amateur-radio-qa-dataset.NEET_2021_QA_Datasetturkish-qa-multi-dialog-dataset
Turkish QA & Multi-Dialog Dataset
Bu depo, iki farklı Türkçe veri kaynağının birleştirilmiş ve temizlenmiş sürümünü içerir:
Yaklaşık 19.000 adet soru-cevap (QA) örneği
Çok adımlı, doğal Türkçe sohbetlerden oluşan diyalog verileri
Bu dataset, hem genel amaçlı Türkçe QA modelleri hem de sohbet/chatbot modelleri için uygundur.
Veri İçeriği
QA Bölümü (~19K)
SQuAD benzeri yapıdan dönüştürülmüş input–output örnekleri
Her satır: tek bir soru ve net bir cevap… See the full description on the dataset page: https://huggingface.co/datasets/sixfingerdev/turkish-qa-multi-dialog-dataset.Knowledge-QA-MultiTurn-Dataset
Knowledge QA Multi-turn Dataset（知識質問データセット・マルチターン）
概要
本データセットは、Aratako/Synthetic-JP-Conversations-Magpie-Nemotron-4-10k から質問を抽出し、DeepSeek V3.2で整形・フォローアップ質問を生成、Kimi K2.5で回答を生成した 3ターンのマルチターン知識質問応答データセット です。Reasoning有効化により思考過程も最終データに含まれ、質問の難易度に応じてReasoning effortが動的に切り替わります。生成にはSDG-LOOMという合成データ生成パイプラインを用いました。（sdg-loom）
データの説明
項目
内容
件数
約3,000件
形式
JSONL（1行1JSON）
言語
日本語
ターン数
3ターン（質問3 + 回答3）
ソースデータセット… See the full description on the dataset page: https://huggingface.co/datasets/DataPilot/Knowledge-QA-MultiTurn-Dataset.JiRack-GammaCorpus-Fact-QA-Datasetmultimodal_qa_dataset_v2_image_focusifc-bim-qa-dataset
IFC BIM Question-Answering Dataset
A comprehensive question-answering dataset for Building Information Modeling (BIM) and Industry Foundation Classes (IFC) domain knowledge.
Dataset Summary
This dataset contains 13,485 question-answer pairs covering comprehensive BIM domain knowledge:
IFC Schema Knowledge: Entities, constraints, functions, and global rules
IFC Documentation: Specifications, concepts, geometry, and processes
Professional Certification: BIM practices… See the full description on the dataset page: https://huggingface.co/datasets/Dietmar2020/ifc-bim-qa-dataset.qa-dataset-k1000
QA Dataset K1000 — The First Drop of Ink
Question-answering data with gold documents and distractor pools for long-context evaluation, accompanying The First Drop of Ink: Nonlinear Impact of Distracting Information in Long-Context Reasoning by Muhan Gao, Zih-Ching Chen, and Kuan-Hao Huang (ICML 2026).
Paper · Full text (v2) · Hugging Face paper page
The paper studies how the proportion of hard distractors affects performance at fixed context length. It reports a nonlinear… See the full description on the dataset page: https://huggingface.co/datasets/lab-flair/qa-dataset-k1000.