datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
deepsearchqa
DeepSearchQA
A 900-prompt factuality benchmark from Google DeepMind, designed to evaluate agents on difficult multi-step information-seeking tasks across 17 different fields.
▶ Google DeepMind Release Blog Post▶ DeepSearchQA Leaderboard on Kaggle▶ Technical Report▶ Evaluation Starter Code
Benchmark
DeepSearchQA is a 900-prompt benchmark for evaluating agents on difficult multi-step information-seeking tasks across 17 different fields. Unlike traditional… See the full description on the dataset page: https://huggingface.co/datasets/google/deepsearchqa.frames-benchmark
FRAMES: Factuality, Retrieval, And reasoning MEasurement Set
FRAMES is a comprehensive evaluation dataset designed to test the capabilities of Retrieval-Augmented Generation (RAG) systems across factuality, retrieval accuracy, and reasoning.
Our paper with details and experiments is available on arXiv: https://arxiv.org/abs/2409.12941.
Dataset Overview
824 challenging multi-hop questions requiring information from 2-15 Wikipedia articles
Questions span diverse topics… See the full description on the dataset page: https://huggingface.co/datasets/google/frames-benchmark.simpleqa-verified
SimpleQA Verified
A 1,000-prompt factuality benchmark from Google DeepMind and Google Research, designed to reliably evaluate LLM parametric knowledge.
▶ SimpleQA Verified Leaderboard on Kaggle▶ Technical Report▶ Evaluation Starter Code
Benchmark
SimpleQA Verified is a 1,000-prompt benchmark for reliably evaluating Large Language Models (LLMs) on short-form factuality
and parametric knowledge. The authors from Google DeepMind and Google Research… See the full description on the dataset page: https://huggingface.co/datasets/google/simpleqa-verified.FACTS-grounding-public
FACTS Grounding 1.0 Public Examples
860 public FACTS Grounding examples from Google DeepMind and Google Research
FACTS Grounding is a benchmark from Google DeepMind and Google Research designed to measure the performance of AI Models on factuality and grounding.
▶ FACTS Grounding Leaderboard on Kaggle▶ Technical Report▶ Evaluation Starter Code▶ Google DeepMind Blog Post
Usage
The FACTS Grounding benchmark evaluates the ability of Large Language Models (LLMs)… See the full description on the dataset page: https://huggingface.co/datasets/google/FACTS-grounding-public.WikiProfile
WikiProfile
WikiProfile is a factual knowledge benchmark for evaluating how well language models encode and recall factual knowledge. It comprises 2,150 facts, each paired with 10 questions, for a total of 21,500 question instances.
Each fact is grounded in the first paragraph (summary) of an English Wikipedia page and is defined as a proposition between two entities, a subject and an object (e.g., "Oasis played their first gig at the Boardwalk club" → subject: Oasis, object:… See the full description on the dataset page: https://huggingface.co/datasets/google/WikiProfile.indian-government-schemes-2025
Indian Government Schemes Dataset 2026
Dataset Description
The most comprehensive structured dataset of Indian central and state government schemes — 4,693 schemes across all ministries and states, with machine-readable eligibility fields.
Maintained by SmartDuke Technologies · Coimbatore, Tamil Nadu, India
This dataset powers SchemeFit — India's government scheme finder for citizens and businesses.
What Makes This Different
Most existing Indian… See the full description on the dataset page: https://huggingface.co/datasets/smartduketech/indian-government-schemes-2025.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.ChatGPT-Jailbreak-Prompts-rubend18
Dataset Card for Dataset Name
Name
ChatGPT Jailbreak Prompts
Dataset Summary
ChatGPT Jailbreak Prompts is a complete collection of jailbreak related prompts for ChatGPT. This dataset is intended to provide a valuable resource for understanding and generating text in the context of jailbreaking in ChatGPT.
Languages
[English]
Global_Environment-Social-And-Governance-Data
Global_Environment-Social-And-Governance Dataset
This Dataset contains all verified and authorized Environment, Social and Governance Statistics data in the World
Description
I have collected all data from WORLD-Bank's Data Catalog and also shared this link in the data source section,
this dataset is sutitable for various NLP tasks
Data Source
https://datacatalog.worldbank.org/
Dataset Card Authors
Mahadi Hassan
Dataset Card Contact… See the full description on the dataset page: https://huggingface.co/datasets/Mahadih534/Global_Environment-Social-And-Governance-Data.reveal
Reveal: A Benchmark for Verifiers of Reasoning Chains
Paper: A Chain-of-Thought Is as Strong as Its Weakest Link: A Benchmark for Verifiers of Reasoning Chains
Link: https://arxiv.org/abs/2402.00559
Website: https://reveal-dataset.github.io/
Abstract:
Prompting language models to provide step-by-step answers (e.g., "Chain-of-Thought") is the prominent approach for complex reasoning tasks, where more accurate reasoning chains typically improve downstream task… See the full description on the dataset page: https://huggingface.co/datasets/google/reveal.indian-government-schemes-2025
Indian Government Schemes Dataset 2026
Dataset Description
The most comprehensive structured dataset of Indian central and state government schemes — 4,693 schemes across all ministries and states, with machine-readable eligibility fields.
Maintained by SmartDuke Technologies · Coimbatore, Tamil Nadu, India
This dataset powers SchemeFit — India's government scheme finder for citizens and businesses.
What Makes This Different
Most existing Indian… See the full description on the dataset page: https://huggingface.co/datasets/Yokey20/indian-government-schemes-2025.ArabicMMLU_full
Fajri Koto, Haonan Li, Sara Shatnawi, Jad Doughman, Abdelrahman Boda Sadallah, Aisha Alraeesi, Khalid Almubarak, Zaid Alyafeai, Neha Sengupta, Shady Shehata, Nizar Habash, Preslav Nakov, and Timothy Baldwin
MBZUAI, Prince Sattam bin Abdulaziz University, KFUPM, Core42, NYU Abu Dhabi, The University of Melbourne
Introduction
We present ArabicMMLU, the first multi-task language understanding benchmark for Arabic language, sourced from school exams across diverse… See the full description on the dataset page: https://huggingface.co/datasets/go-inoue/ArabicMMLU_full.goatBitext-customer-support-llm-chatbot-training-dataset
Bitext - Customer Service Tagged Training Dataset for LLM-based Virtual Assistants
Overview
This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the Customer Support sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/gorges-haha/Bitext-customer-support-llm-chatbot-training-dataset.TACT
TACT: A Complex Numerical Reasoning Benchmark
Paper - TACT: Advancing Complex Aggregative Reasoning with Information Extraction Tools
Website: https://tact-benchmark.github.io
Abstract: Large Language Models (LLMs) often do not perform well on queries that require the aggregation of information across texts. To better evaluate this setting and facilitate modeling efforts, we introduce TACT - Text And Calculations through Tables, a dataset crafted to evaluate LLMs'… See the full description on the dataset page: https://huggingface.co/datasets/google/TACT.dataset-qa-ip-lawДатасет для оценки производительности большой языковой модели.
Контрибьюторы (в алфавитном порядке):
Ася Айнбунд
Дарья Анисимова
Юрий Батраков
Арсений Батуев
Егор Батурин
Андрей Бочков
Дмитрий Данилов
Максим Долотин
Алексей Дружинин
Константин Евменов
Лолита Князева
Владимир Королев
Антон Костин
Ярослав Котов
Сергей Лагутин
Иван Литвак
Илья Лопатин
Татьяна Максиян
Артур Маликов
Александр Медведев
Михаил
Кирилл Пантелеев
Александр Панюков
Алексей Суслов
Даниэль Торен
Данила Хайдуков… See the full description on the dataset page: https://huggingface.co/datasets/lawful-good-project/dataset-qa-ip-law.indian-government-schemes-2025
Indian Government Schemes Dataset 2026
Dataset Description
The most comprehensive structured dataset of Indian central and state government schemes — 4,693 schemes across all ministries and states, with machine-readable eligibility fields.
Maintained by SmartDuke Technologies · Coimbatore, Tamil Nadu, India
This dataset powers SchemeFit — India's government scheme finder for citizens and businesses.
What Makes This Different
Most existing Indian… See the full description on the dataset page: https://huggingface.co/datasets/siva0072/indian-government-schemes-2025.indian-government-schemes-2025
Indian Government Schemes Dataset 2026
Dataset Description
The most comprehensive structured dataset of Indian central and state government schemes — 4,693 schemes across all ministries and states, with machine-readable eligibility fields.
Maintained by SmartDuke Technologies · Coimbatore, Tamil Nadu, India
This dataset powers SchemeFit — India's government scheme finder for citizens and businesses.
What Makes This Different
Most existing Indian… See the full description on the dataset page: https://huggingface.co/datasets/Sumna/indian-government-schemes-2025.go-reasoningSamples in this benchmark were generated by RELAI using the following data source(s):
Data Source Name: Go
Documentation Data Source Link: https://go.dev/doc/
Data Source License: https://go.dev/LICENSE
Data Source Authors: Go Contributors
AI Benchmarks by Data Agents © 2025 RELAI.AI · Licensed under CC BY 4.0. Source: https://relai.ai
MS_MARCO_Gold_Passage_QA
How to Make
Make "Question has only one answer".
If Question has multiple answer, that question is deleted.
Example Usage
from datasets import load_dataset
docs = load_dataset('jun000/MS_MARCO_Gold_Passage_QA')
azerbaijani-gov-qa
Azerbaijani Government Services Question Answering Dataset
Overview
This dataset contains over 5000 samples of question-answer pairs scraped from the comments section of the Instagram page of AsanXidmat, a government organization in Azerbaijan dedicated to providing services to Azerbaijani citizens. The dataset is intended for use in training and evaluating question answering systems, particularly those focused on understanding and responding to inquiries related to… See the full description on the dataset page: https://huggingface.co/datasets/arzumanabbasov/azerbaijani-gov-qa.power-seeking-eval-300
Power-Seeking Evaluation Dataset
A 300-item multiple-choice benchmark for power-seeking in language models: the
disposition to prefer options that increase the model's resources, autonomy,
influence, or freedom from oversight, in situations where a lower-power option
would serve the stated task equally well.
Model-written, following Perez et al.,
"Discovering Language Model Behaviors with Model-Written Evaluations".
Built for the ARENA LLM
evaluations curriculum.
This is the… See the full description on the dataset page: https://huggingface.co/datasets/GodwillN/power-seeking-eval-300.ArabicMMLU_undiac
Fajri Koto, Haonan Li, Sara Shatnawi, Jad Doughman, Abdelrahman Boda Sadallah, Aisha Alraeesi, Khalid Almubarak, Zaid Alyafeai, Neha Sengupta, Shady Shehata, Nizar Habash, Preslav Nakov, and Timothy Baldwin
MBZUAI, Prince Sattam bin Abdulaziz University, KFUPM, Core42, NYU Abu Dhabi, The University of Melbourne
Introduction
We present ArabicMMLU, the first multi-task language understanding benchmark for Arabic language, sourced from school exams across diverse… See the full description on the dataset page: https://huggingface.co/datasets/go-inoue/ArabicMMLU_undiac.go-standardSamples in this benchmark were generated by RELAI using the following data source(s):
Data Source Name: Go
Documentation Data Source Link: https://go.dev/doc/
Data Source License: https://go.dev/LICENSE
Data Source Authors: Go Contributors
AI Benchmarks by Data Agents © 2025 RELAI.AI · Licensed under CC BY 4.0. Source: https://relai.ai
kanna-rag-gold-standard
Kanna RAG Gold Standard Dataset
This dataset contains 30 expert-curated Question-Answer pairs focused on the ethnopharmacology of Sceletium tortuosum (Kanna). It serves as the "Gold Standard" evaluation set for the LAYRA (Large Academic Visual RAG Agent) thesis project.
Dataset Structure
query: The scientific question.
doc_id: The unique identifier of the source document (PDF).
page_num: The specific page number where the answer is found (critical for Visual RAG).… See the full description on the dataset page: https://huggingface.co/datasets/SAINTHALF/kanna-rag-gold-standard.indian-government-schemes-2025
Indian Government Schemes Dataset 2026
Dataset Description
The most comprehensive structured dataset of Indian central and state government schemes — 4,693 schemes across all ministries and states, with machine-readable eligibility fields.
Maintained by SmartDuke Technologies · Coimbatore, Tamil Nadu, India
This dataset powers SchemeFit — India's government scheme finder for citizens and businesses.
What Makes This Different
Most existing Indian… See the full description on the dataset page: https://huggingface.co/datasets/har123ish/indian-government-schemes-2025.