datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
trivia_qa
Dataset Card for "trivia_qa"
Dataset Summary
TriviaqQA is a reading comprehension dataset containing over 650K
question-answer-evidence triples. TriviaqQA includes 95K question-answer
pairs authored by trivia enthusiasts and independently gathered evidence
documents, six per question on average, that provide high quality distant
supervision for answering the questions.
Supported Tasks and Leaderboards
More Information Needed
Languages… See the full description on the dataset page: https://huggingface.co/datasets/mandarjoshi/trivia_qa.Omni-Frontier-Distillation-SFT-Cyber-Coding-Med-dataset-collection
🌌 Omni-Frontier Distillation SFT
The Definitive Evolution of Open-Source Distillation & Human-Crafted Expertise
Repository: Manusagents/Omni-Frontier-Distillation-SFT-Cyber-Coding-Med-dataset-collection
"The most comprehensive multi‑domain SFT corpus ever assembled — fusing 6.86 million cleaned distillation samples with 9.14 million human‑crafted expert examples across medical, cybersecurity, chemical, robotics, humanities, and more. 16 million… See the full description on the dataset page: https://huggingface.co/datasets/Manusagents/Omni-Frontier-Distillation-SFT-Cyber-Coding-Med-dataset-collection.PulseLM
PulseLM: A Foundation Dataset and Benchmark for PPG-Text Learning
Usage
from datasets import load_dataset, get_dataset_config_names, concatenate_datasets # datasets==4.5.0
dataset_names = get_dataset_config_names("Manhph2211/PulseLM")
print(f"Available datasets: {dataset_names}")
train_splits = [
load_dataset("Manhph2211/PulseLM", name, split="train").select_columns(["signal", "text", "qa"])
for name in dataset_names
]
combined =… See the full description on the dataset page: https://huggingface.co/datasets/Manhph2211/PulseLM.Mantis-Eval
Overview
This is a newly curated dataset to evaluate multimodal language models' capability to reason over multiple images. More details are shown in https://tiger-ai-lab.github.io/Mantis/.
Statistics
This evaluation dataset contains 217 human-annotated challenging multi-image reasoning problems.
Leaderboard
We list the current results as follows:
Models
Size
Mantis-Eval
LLaVA OneVision
72B
77.60
LLaVA OneVision
7B
64.20
GPT-4V
-
62.67… See the full description on the dataset page: https://huggingface.co/datasets/TIGER-Lab/Mantis-Eval.Omni-Frontier-Distillation-SFT-Cyber-security-Coding-dataset-collection-v2
🧬 Omni-Frontier Collection
Cybersecurity · Coding · Math · Science · RSI Reasoning — one unified SFT package
A unified, deduplicated, fully-browsable distillation & SFT corpus — every row real, every row visible.
📖 Jump to
What's inside · 🔁 Aggregation audit · 🛡 Cybersecurity · 💻 Coding · 🏭 Distillation deep-dive · 🔁 RSI · 🧮 Math/Science/More · 🎓 Training guide · 🔎 Browsing · 🧹 Quality · 🗺 Roadmap · 📄 License… See the full description on the dataset page: https://huggingface.co/datasets/Manusagents/Omni-Frontier-Distillation-SFT-Cyber-security-Coding-dataset-collection-v2.updesh_updated
📢 Updesh: Synthetic Multilingual Instruction Tuning Dataset for 13 Indic Languages
NOTE: This is an initial $\beta$-release. We plan to release subsequent versions of Updesh with expanded coverage and enhanced quality control. Future iterations will include larger datasets, improved filtering pipelines.
Updesh is a large-scale synthetic dataset designed to advance post-training of LLMs for Indic languages. It integrates translated reasoning data and synthesized open-domain… See the full description on the dataset page: https://huggingface.co/datasets/manan-u/updesh_updated.fquad2_test
Dataset Card for "Fquad2_test"
This dataset is released as part of FrenchBench, a benchmarking initiative for French Language Model evaluation.
It can be used for extractive QA, binary classifcation or infiormation retrieving evaluation !
Cite
@misc{faysse2024croissantllm,
title={CroissantLLM: A Truly Bilingual French-English Language Model},
author={Manuel Faysse and Patrick Fernandes and Nuno M. Guerreiro and António Loison and Duarte M. Alves and Caio… See the full description on the dataset page: https://huggingface.co/datasets/manu/fquad2_test.Manalyzer
Manalyzer: End-to-end Automated Meta-analysis with Multi-agent System
🆕 Updates/News
🚩 Updates (2026-02-09) Code has been released.
🚩 Updates (2025-05-22) Initial upload to arXiv [PDF]. The code will be released soon.
🎯 Abstract
Meta-analysis is a systematic research methodology that synthesizes data from multiple existing studies to derive comprehensive conclusions. This approach not only mitigates limitations inherent in individual studies but also… See the full description on the dataset page: https://huggingface.co/datasets/black-yt/Manalyzer.verified-math-code-17k
Verified Math & Code, 17,000 rows
A math and code instruction dataset where every single row was mechanically checked before it was
allowed in. Not filtered by a heuristic, not scored by a model. Checked.
Two layers of verification, one per domain:
Every math answer was compared against an independent gold answer by exact, numeric and
symbolic (SymPy) comparison. If the worked solution did not arrive at the gold answer, the row
was dropped.… See the full description on the dataset page: https://huggingface.co/datasets/manifesta/verified-math-code-17k.MANTA-1M
Abstract
We introduce MANTA, an automated pipeline that generates high-quality large-scale instruction fine-tuning datasets from massive web corpora while preserving their diversity and scalability. By extracting structured syllabi from web documents and leveraging high-performance LLMs, our approach enables highly effective query-response generation with minimal human intervention. Extensive experiments on 8B-scale LLMs demonstrate that fine-tuning on the MANTA-1M dataset… See the full description on the dataset page: https://huggingface.co/datasets/LGAI-EXAONE/MANTA-1M.MortarBench
MortarBench
A benchmark for evaluating LLM agents on mortgage loan origination. Each item
gives an agent two synthetic source documents - a bank statement (Plaid-format
JSON) and a completed loan application (ULAD/MISMO XML) - and asks an
underwriting question that can only be answered by cross-referencing them.
Paper: https://arxiv.org/abs/2606.19416
OpenReview: https://openreview.net/forum?id=EMdAVOU3Rr
Code: https://github.com/mtoles/MortarBench
Why it is hard… See the full description on the dataset page: https://huggingface.co/datasets/ManavMunjal/MortarBench.Data-Analytics-Digital-Marketing-Project-Management-QA_DBmantinc-catalan-drift
Mantinc — Catalan Drift Benchmark
Descripció (ca)
Mantinc és un banc de proves que avalua si un model de llenguatge continua
responent en català quan el missatge, la conversa prèvia o el context recuperat
l'empenyen a fer-ho en una altra llengua, normalment el castellà o l'anglès.
Dataset Description
Mantinc is a benchmark that measures whether a language model keeps answering
in Catalan when the prompt, prior conversation, or retrieved context… See the full description on the dataset page: https://huggingface.co/datasets/softcatala/mantinc-catalan-drift.MoBiPlant
Dataset Card for MoBiPlant
Dataset Summary
MoBiPlant is a multiple-choice question-answering dataset curated by plant molecular biologists worldwide. It comprises two merged versions:
Expert MoBiPlant: 565 expert-level questions authored by leading researchers.
Synthetic MoBiPlant: 1,075 questions generated by large language models from papers in top plant science journals.
Each example consists of a question about plant molecular biology, a set of answer… See the full description on the dataset page: https://huggingface.co/datasets/manufernandezbur/MoBiPlant.actuarial-global-glossary-multilingual
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Join the mission to make actuarial knowledge accessible worldwide
Let's discuss how AI can transform professional education and break language barriers in finance!
🌍 Global Actuarial Glossary - Breaking Language Barriers in Finance
🚀 The World's Most Comprehensive Multilingual Actuarial Dataset
Imagine: A brilliant actuarial student in Tokyo, a risk analyst in São Paulo, and an insurance executive… See the full description on the dataset page: https://huggingface.co/datasets/manuelcaccone/actuarial-global-glossary-multilingual.Bitext-wealth-management-llm-chatbot-training-dataset
Bitext - Wealth Management 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 [Wealth Management] sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-wealth-management-llm-chatbot-training-dataset.verified-agronomy-17k
Verified Agronomy, 17,199 rows
The arithmetic a working agronomist actually does: fertiliser rates, growing degree days,
irrigation scheduling, seeding rates, grain moisture, sprayer calibration, forage budgeting.
Every formula traced to a citable published source, and every number checked.
And 1,796 rows (10.4%) that cannot be answered at all, where the correct response is to say so
and name the missing input.
Verify this card… See the full description on the dataset page: https://huggingface.co/datasets/manifesta/verified-agronomy-17k.ManagerBench
ManagerBench
ManagerBench is a benchmark designed to evaluate the decision-making capabilities of large language models (LLMs) as they evolve from conversational assistants into autonomous agents. ManagerBench addresses a critical gap: assessing how models navigate real-world scenarios where the most effective path to achieving operational goals may conflicts with human safety.
Dataset Details
The benchmark evaluates models through realistic, human-validated managerial… See the full description on the dataset page: https://huggingface.co/datasets/AdiSimhi/ManagerBench.SciRecipe
🧪 SciRecipe
A structured dataset for scientific experimental protocol generation,designed to model experiments as executable and verifiable workflows rather than free-form text.
📌 Overview
SciRecipe focuses on a key limitation of current large language models:
protocols may look correct, but often cannot be executed in real laboratories.
To address this, SciRecipe represents experimental procedures with explicit structure, reasoning, and ordering, enabling both… See the full description on the dataset page: https://huggingface.co/datasets/manglu3935/SciRecipe.MSD_manual_topics_user_base
MSD_manual_topics_user_base
This dataset has been built with the website https://www.msdmanuals.com/ provided by Merck & Co for the greater audience.
The MSD manual is an essential source of knowledge for many topics related to symptoms, diseases, health and other related topics. The manual makes an extra effort to make it available both for professionals and patients by having two distinct version.
The content, while being labelled the same, differs by the type of user in order to… See the full description on the dataset page: https://huggingface.co/datasets/nuvocare/MSD_manual_topics_user_base.actuarial-gpt-conversations
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Manuel Caccone - Actuarial Data Scientist & Open Source Educator
Let's discuss actuarial science, AI, and open source projects!
📊 ActuarialGPT Conversations Dataset
Precision Mathematical Conversations for Insurance Intelligence
🎯 Quick Facts
Feature
Description
Domain
Actuarial Science, Insurance Analytics, Risk Management
Language
English (Technical/Expert Level)… See the full description on the dataset page: https://huggingface.co/datasets/manuelcaccone/actuarial-gpt-conversations.sql-new-copy
Languages:
English
Data Splits
The following is taken from the corpus' source repsository:
mandela-speech-corpus
🇿🇦 Nelson Mandela Lifetime Speech & Lecture Corpus (1951–2010)
A comprehensive, clean, verified, machine-readable dataset comprising the complete lifetime speeches, parliamentary addresses, international keynotes, university convocations, and trial statements delivered by Nelson Rolihlahla Mandela across 6 decades (1951–2010).
📊 Dataset Statistics
Metric
Value
Total Canonical Speeches
1,000
Total Raw Source Records
1,000
Total Word Count
1… See the full description on the dataset page: https://huggingface.co/datasets/sanjeevafk/mandela-speech-corpus.OMB-Circular-A-123-Management-Responsibility-for-Risk-Management-and-Internal-Controls
OMB Circular A-123 Enterprise Risk Management and Internal Control Question Answering Dataset
Dataset Summary
Maintainer: Terry Eppler
Ownership: US Federal Government
The OMB Circular A-123 Enterprise Risk Management and Internal Control Question
Answering Dataset is a synthetic instruction-style question-answering dataset
derived from OMB Circular No. A-123, Management’s Responsibility for
Enterprise Risk Management and Internal Control.
The dataset is… See the full description on the dataset page: https://huggingface.co/datasets/leeroy-jankins/OMB-Circular-A-123-Management-Responsibility-for-Risk-Management-and-Internal-Controls.claude-opus-4.6-4.7-reasoning-8.7k
Background
Ended up with some tokens to burn on a Claude Max plan. Assembly began during 4.6 and moved to 4.7. Model is tagged. The development evolved as it went along. The dataset has not been manually reviewed. It's entirely Claude developed.
Clarification on Reasoning
The reasoning is not Claude's actual chain-of-thought (cot) and is not summarized cot. It's a fully synthetic cot created as part of the Assistant response to mimic the type of "thinking"… See the full description on the dataset page: https://huggingface.co/datasets/manojdahal191gom/claude-opus-4.6-4.7-reasoning-8.7k.doc2instruct-holdout-qa
doc2instruct Held-out QA (Research Preview)
A 150-item reading-comprehension set over 15 arXiv papers that were excluded
from all training data. It exists to measure grounded document QA, and in
particular whether cross-page (multi-hop) items are actually unanswerable
from a single page.
This is a research preview, not a leaderboard benchmark. Every item is
mechanically gated (review = machine_gate). It has not been
hand-verified. Do not describe it as human-annotated.
Code and… See the full description on the dataset page: https://huggingface.co/datasets/mangesh-ux/doc2instruct-holdout-qa.ChronoInstruct-SFT-v1
Dataset Summary
ChronoInstruct-SFT is the first chronologically consistent instruction-following dataset designed to remove lookahead bias in large language models.Each prompt–response pair is verified to contain only knowledge available before the year 2000, ensuring that no future information leaks into training.
The dataset was constructed as part of the paper:
Songrun He, Linying Lv, Asaf Manela, Jimmy Wu (2025). “Chronologically Consistent Generative AI.”Washington University… See the full description on the dataset page: https://huggingface.co/datasets/manelalab/ChronoInstruct-SFT-v1.cybersecurity-qa-v2
Cybersecurity Q&A Dataset v2 — 2.6M Examples
A large-scale cybersecurity Q&A dataset for fine-tuning LLMs on security topics.
2,621,468 examples covering vulnerabilities, attack techniques, weaknesses, and defensive strategies.
Statistics
Source
Examples
Description
NIST NVD CVE Database
~1,954,225
All CVEs (2002–2025): overview, severity, detection, remediation
AlicanKiraz0/All-CVE-Records-Training-Dataset
~297,441
Detailed CVE analysis with markdown… See the full description on the dataset page: https://huggingface.co/datasets/Manusagents/cybersecurity-qa-v2.DoD-Instruction-6055-17-Emergency-Management-Program
🚨 DoD Emergency Management Program
Maintainer: Terry Eppler
Owner: US Federal Government
Source: DoD Instruction 6055.17
Source Version: Change 4, effective December 1, 2025
Ownership of Source: United States Department of Defense
📋 Overview
Dataset Summary
The DoD Emergency Management Program Question-Answer Dataset is a structured, document-grounded natural-language dataset derived from DoD Instruction 6055.17, “DoD Emergency… See the full description on the dataset page: https://huggingface.co/datasets/leeroy-jankins/DoD-Instruction-6055-17-Emergency-Management-Program.historical-training-manuals
Historical Training Manuals
1,597 US government and government-adjacent training manuals and technical publications
sourced from the Internet Archive, spanning roughly 1800-2021. Records carry
bibliographic metadata; a subset also carries extracted full text and a machine-generated
summary.
Loading
from datasets import load_dataset
ds = load_dataset("robworks-software/historical-training-manuals")
Splits
Split
Rows
train
1,277… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/historical-training-manuals.