datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
megawikaMegaWika is a multi- and crosslingual text dataset containing 30 million
Wikipedia passages with their scraped and cleaned web citations. The
passages span 50 Wikipedias in 50 languages, and the articles in which
the passages were originally embedded are included for convenience. Where
a Wikipedia passage is in a non-English language, an automated English
translation is provided. Furthermore, nearly 130 million English
question/answer pairs were extracted from the passages, and FrameNet events
occurring in the passages are detected using the LOME FrameNet parser.megalith-mdqa
Images from Megalith, synthetically captioned using Moondream, with the questions then transformed to short-form QA using an LLM.
VDR_MEGA_2
VDR_MEGA_2
Dataset Summary
VDR_MEGA_2 is a high-quality multimodal dataset created through the merge of multiple domain-specific datasets with enhanced data processing techniques. This dataset represents our most refined approach to multimodal data generation, incorporating filtering algorithms and improved AI-assisted content generation to deliver superior quality for RAG, DSE, question answering, document search, and vision-language model training tasks.… See the full description on the dataset page: https://huggingface.co/datasets/racineai/VDR_MEGA_2.Mega60k
Mega60k: Chart Question Answering Dataset
Dataset Overview
A multimodal chart question answering dataset featuring charts in multiple formats (CSV, PNG, SVG) and degraded PNG images with components omission, occlusion, blurring, and rotation to enhance robustness evaluation.
Languages: English
Chart Type Distribution
Chart Type
Count
Chart Type
Count
Chart Type
Count
Area
200
Bar
200
Box
200
Bubble
200
Chord
200
Fill-bubble
200
Funnel
200… See the full description on the dataset page: https://huggingface.co/datasets/guodaosun/Mega60k.Medical-Reasoning-SFT-Mega
Medical-Reasoning-SFT-Mega
The ultimate medical reasoning dataset - combining 7 state-of-the-art AI models with fair distribution deduplication. 1.79 million unique samples with 3.78 billion tokens of medical chain-of-thought reasoning.
Dataset Overview
Metric
Value
Total Samples
1,789,998 (after deduplication)
Total Tokens
~3.78 Billion
Content Tokens
~2.22 Billion
Reasoning Tokens
~1.56 Billion
Samples with Reasoning
1,789,764 (100.0%)
Unique… See the full description on the dataset page: https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-Mega.subjqaSubjQA is a question answering dataset that focuses on subjective questions and answers.
The dataset consists of roughly 10,000 questions over reviews from 6 different domains: books, movies, grocery,
electronics, TripAdvisor (i.e. hotels), and restaurants.MEGA-Bench
MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks [ICLR 2025]
🌐 Homepage | 🏆 Leaderboard | 🤗 Dataset | 🤗 Paper | 🔎 Visualiaztion | 📖 arXiv | GitHub
🔔 News
[2025-01]: Paper accepted by ICLR 2025.
[2024-10-18]: Initial release of the evaluation code on our Github repo.
[2024-10-14]: Paper released on arXiv.
❗❗ Data Information
We put the file path of images/videos in HF datasets. Please download the zipped data here.
We chose… See the full description on the dataset page: https://huggingface.co/datasets/TIGER-Lab/MEGA-Bench.Twin-2K-500-Mega-Study
Twin-2K-500-Mega-Study Dataset
GitHub Repository: https://github.com/TianyiPeng/Twin-2K-500-Mega-Study
To see more details for how to process these data, please refer to this GitHub repository.
This dataset contains survey data from the Twin-2K-500 Mega Study, which tests the validity of using large language models to predict people's future answers based on their answers to past surveys (creating "digital twins" of participants).
Dataset Structure
The dataset is… See the full description on the dataset page: https://huggingface.co/datasets/LLM-Digital-Twin/Twin-2K-500-Mega-Study.holobench
HoloBench (Holistic Reasoning Benchmark)
HoloBench is a benchmark designed to evaluate the ability of long-context language models (LCLMs) to perform holistic reasoning over extended text contexts.
Unlike standard models that retrieve isolated information, HoloBench tests how well LCLMs handle complex reasoning tasks that require aggregating and synthesizing information across multiple documents or large text segments.
Dataset Details
Dataset Description… See the full description on the dataset page: https://huggingface.co/datasets/megagonlabs/holobench.Medical-Reasoning-SFT-Mega
Medical-Reasoning-SFT-Mega
The ultimate medical reasoning dataset - combining 7 state-of-the-art AI models with fair distribution deduplication. 1.79 million unique samples with 3.78 billion tokens of medical chain-of-thought reasoning.
Dataset Overview
Metric
Value
Total Samples
1,789,998 (after deduplication)
Total Tokens
~3.78 Billion
Content Tokens
~2.22 Billion
Reasoning Tokens
~1.56 Billion
Samples with Reasoning
1,789,764 (100.0%)
Unique… See the full description on the dataset page: https://huggingface.co/datasets/Sidd2229/Medical-Reasoning-SFT-Mega.Medical-Reasoning-SFT-Mega
Medical-Reasoning-SFT-Mega
The ultimate medical reasoning dataset - combining 7 state-of-the-art AI models with fair distribution deduplication. 1.79 million unique samples with 3.78 billion tokens of medical chain-of-thought reasoning.
Dataset Overview
Metric
Value
Total Samples
1,789,998 (after deduplication)
Total Tokens
~3.78 Billion
Content Tokens
~2.22 Billion
Reasoning Tokens
~1.56 Billion
Samples with Reasoning
1,789,764 (100.0%)
Unique… See the full description on the dataset page: https://huggingface.co/datasets/dhruvR16/Medical-Reasoning-SFT-Mega.MegaWikiQA-v1-multihop
MegaWikiQA v1 Multihop Dataset
Combined and shuffled Wiki5M-based synthetic multihop QA dataset for hypernetwork / knowledge-injection research.
Sources
Hop
Source dataset
Rows
1
nace-ai/wiki5m_1hop_qa_pairs_1M_stratified_with_domain
1,000,000
2
nace-ai/wiki5m_2hop_qa_pairs_noun_v10_domain
1,894,483
3
nace-ai/wiki5m_3hop_qa_pairs_noun_v10_domain
2,393,688
Total
shuffled (seed=42)
5,288,171
Schema
question, answer
hop — 1 / 2 /… See the full description on the dataset page: https://huggingface.co/datasets/nace-ai/MegaWikiQA-v1-multihop.ZamAI-Pashto-Mega-Dataset
ZamAI Pashto Mega Dataset
Languages: psLicense: apache-2.0Task categories: text-generation, summarization, question-answeringSize categories: 1M<n<10M
Summary
This dataset is part of the ZamAI Pashto data collection. It is intended for text-generation, summarization, question-answering tasks in Pashto.
How to use
from datasets import load_dataset
dataset = load_dataset("tasal9/ZamAI-Pashto-Mega-Dataset")
print(dataset)
Configs… See the full description on the dataset page: https://huggingface.co/datasets/tasal9/ZamAI-Pashto-Mega-Dataset.Medical-Reasoning-SFT-Mega
Medical-Reasoning-SFT-Mega
The ultimate medical reasoning dataset - combining 7 state-of-the-art AI models with fair distribution deduplication. 1.79 million unique samples with 3.78 billion tokens of medical chain-of-thought reasoning.
Dataset Overview
Metric
Value
Total Samples
1,789,998 (after deduplication)
Total Tokens
~3.78 Billion
Content Tokens
~2.22 Billion
Reasoning Tokens
~1.56 Billion
Samples with Reasoning
1,789,764 (100.0%)
Unique… See the full description on the dataset page: https://huggingface.co/datasets/introvoyz041/Medical-Reasoning-SFT-Mega.megatrendit-2026
Sitra Megatrendit 2026 Dataset
This dataset contains the structured content from Sitra's Megatrends 2026 report (Megatrendit 2026 - Kohti uutta yhteiskuntasopimusta).
Why was this dataset created?
Sitra's Megatrends report is a key Finnish foresight publication that analyzes global trends shaping society over the next decade. The original report is published as a PDF, which is not an optimal format for LLMs, RAG, and other machine usages.
This dataset was created to:… See the full description on the dataset page: https://huggingface.co/datasets/sitrafund/megatrendit-2026.MEGA-cleaned-prompts
Cleaned Prompts Mega Dataset
Created by Aipresso LIMITED, London, UK
⚠️ IMPORTANT: By using this dataset, you agree to our Terms of Use
You must provide attribution when using this data in publications, research, or commercial products.
Dataset Overview
A comprehensive collection of 2.7 million cleaned English prompts, meticulously processed for training advanced language models and AI systems.
📊 Dataset Statistics
Metric
Value
Total Rows
2,689… See the full description on the dataset page: https://huggingface.co/datasets/Aipresso/MEGA-cleaned-prompts.Medical-Reasoning-SFT-Mega
Medical-Reasoning-SFT-Mega
The ultimate medical reasoning dataset - combining 7 state-of-the-art AI models with fair distribution deduplication. 1.79 million unique samples with 3.78 billion tokens of medical chain-of-thought reasoning.
Dataset Overview
Metric
Value
Total Samples
1,789,998 (after deduplication)
Total Tokens
~3.78 Billion
Content Tokens
~2.22 Billion
Reasoning Tokens
~1.56 Billion
Samples with Reasoning
1,789,764 (100.0%)
Unique… See the full description on the dataset page: https://huggingface.co/datasets/Dragnoz/Medical-Reasoning-SFT-Mega.demons_megaten_fandom_orpo_dpo_englishMedical-Reasoning-SFT-Mega
Medical-Reasoning-SFT-Mega
The ultimate medical reasoning dataset - combining 7 state-of-the-art AI models with fair distribution deduplication. 1.79 million unique samples with 3.78 billion tokens of medical chain-of-thought reasoning.
Dataset Overview
Metric
Value
Total Samples
1,789,998 (after deduplication)
Total Tokens
~3.78 Billion
Content Tokens
~2.22 Billion
Reasoning Tokens
~1.56 Billion
Samples with Reasoning
1,789,764 (100.0%)
Unique… See the full description on the dataset page: https://huggingface.co/datasets/CrossNow/Medical-Reasoning-SFT-Mega.ZamAI-Pashto-MegaDataset-v1
ZamAI Pashto Mega Dataset v1
Languages: psLicense: apache-2.0Task categories: text-generation, summarization, question-answeringSize categories: 10K<n<100K
Summary
This dataset is part of the ZamAI Pashto data collection. It is intended for text-generation, summarization, question-answering tasks in Pashto.
How to use
from datasets import load_dataset
dataset = load_dataset("tasal9/ZamAI-Pashto-MegaDataset-v1")
print(dataset)
Configs… See the full description on the dataset page: https://huggingface.co/datasets/tasal9/ZamAI-Pashto-MegaDataset-v1.Medical-Reasoning-SFT-Mega
Medical-Reasoning-SFT-Mega
The ultimate medical reasoning dataset - combining 7 state-of-the-art AI models with fair distribution deduplication. 1.79 million unique samples with 3.78 billion tokens of medical chain-of-thought reasoning.
Dataset Overview
Metric
Value
Total Samples
1,789,998 (after deduplication)
Total Tokens
~3.78 Billion
Content Tokens
~2.22 Billion
Reasoning Tokens
~1.56 Billion
Samples with Reasoning
1,789,764 (100.0%)
Unique… See the full description on the dataset page: https://huggingface.co/datasets/living-my-best-life/Medical-Reasoning-SFT-Mega.Medical-Reasoning-SFT-Mega
Medical-Reasoning-SFT-Mega
The ultimate medical reasoning dataset - combining 7 state-of-the-art AI models with fair distribution deduplication. 1.79 million unique samples with 3.78 billion tokens of medical chain-of-thought reasoning.
Dataset Overview
Metric
Value
Total Samples
1,789,998 (after deduplication)
Total Tokens
~3.78 Billion
Content Tokens
~2.22 Billion
Reasoning Tokens
~1.56 Billion
Samples with Reasoning
1,789,764 (100.0%)
Unique… See the full description on the dataset page: https://huggingface.co/datasets/jumpzakrab/Medical-Reasoning-SFT-Mega.Medical-Reasoning-SFT-Mega
Medical-Reasoning-SFT-Mega
The ultimate medical reasoning dataset - combining 7 state-of-the-art AI models with fair distribution deduplication. 1.79 million unique samples with 3.78 billion tokens of medical chain-of-thought reasoning.
Dataset Overview
Metric
Value
Total Samples
1,789,998 (after deduplication)
Total Tokens
~3.78 Billion
Content Tokens
~2.22 Billion
Reasoning Tokens
~1.56 Billion
Samples with Reasoning
1,789,764 (100.0%)
Unique… See the full description on the dataset page: https://huggingface.co/datasets/mk12333/Medical-Reasoning-SFT-Mega.