datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.Edge-Agent-Reasoning-WebSearch-260K
Edge Agent Reasoning WebSearch 260K
Abstract
The Edge-Agent-Reasoning-WebSearch-260K dataset is a massive, synthetically expert-engineered corpus of over 700 Million tokens, designed to train small, local models (SLMs) and edge-deployed agents in advanced problem deconstruction and self-aware reasoning.
Rather than training a model to execute instructions directly—which often leads to hallucinations when context is missing—this dataset trains a model to act as a… See the full description on the dataset page: https://huggingface.co/datasets/yatin-superintelligence/Edge-Agent-Reasoning-WebSearch-260K.WebInstructSub
🦣 MAmmoTH2: Scaling Instructions from the Web
Project Page: https://tiger-ai-lab.github.io/MAmmoTH2/
Paper: https://arxiv.org/pdf/2405.03548
Code: https://github.com/TIGER-AI-Lab/MAmmoTH2
WebInstruct (Subset)
This repo contains the partial dataset used in "MAmmoTH2: Scaling Instructions from the Web". This partial data is coming mostly from the forums like stackexchange. This subset contains very high-quality data to boost LLM performance through instruction tuning.… See the full description on the dataset page: https://huggingface.co/datasets/TIGER-Lab/WebInstructSub.web-bench
🤗 HuggingFace ｜ Slack | WeChat
Web-Bench: Unified DeepResearch Benchmarks
A curated collection of widely used deep research benchmarks in a unified format, including BrowseComp-Plus, BrowseComp, GAIA, xbench-DeepSearch, SEAL, HLE, for OpenResarcher-30B-A3B evaluation.
📑 Table of Contents
Dataset Overview
Unified Format
Usage
Dataset Details
1. HLE (Humanity's Last Exam)
2. GAIA-text (Text-only GAIA)
3.… See the full description on the dataset page: https://huggingface.co/datasets/OpenResearcher/web-bench.securecode-web
SecureCode Web: Traditional Web & Application Security Dataset
Production-grade web security vulnerability dataset with complete incident grounding, 4-turn conversational structure, and comprehensive operational guidance
Paper | GitHub | Dataset | Model Collection | Blog Post
What's new in v2.6
v2.6 restores proper Express.js coverage for the topics whose examples were removed in v2.5.1 (they had
shared one reused answer). 29 new, genuinely distinct Express.js… See the full description on the dataset page: https://huggingface.co/datasets/scthornton/securecode-web.cocis-web-info
COCIS WEB INFO
Dataset Summary
This dataset contains information about Makerere University College of Computing and Information Science that was scraped from its official website and corresponding websites.
The dataset consists of approximately 513 JSON chunks, designed for high-performance streaming and parallel processing. Each chunk represents a discrete unit of data structured for machine learning tasks.
By sharding the data into 513 files, this repository supports… See the full description on the dataset page: https://huggingface.co/datasets/jimjunior/cocis-web-info.WebForge
WebForge-Bench
WebForge-Bench is a browser agent benchmark containing 934 tasks across 7 domains and 3 difficulty levels, generated by the WebForge automated pipeline.
Every task is a self-contained static website — no external services, databases, or APIs needed. Just serve the HTML files and point your agent at them.
Dataset Summary
Property
Value
Total tasks
934
Domains
7 (Consumer Transaction, Content Moderation, Enterprise Process, Info… See the full description on the dataset page: https://huggingface.co/datasets/yuandaxia/WebForge.WebWalkerQA📑 The paper of WebWalkerQA is available at arXiv.
📊 The dataset resource is a collection of 680 questions and answers from the WebWebWalker dataset.
🙋 The dataset is in the form of a JSON file.
The keys in the JSON include:
Question, Answer, Root_Url, and Info. The Info field contains
more detailed information, including Hop, Domain, Language,
Difficulty_Level, Source Website, and Golden_Path.
{
"Question": "When is the paper submission deadline for the ACL 2025 Industry Track, and what… See the full description on the dataset page: https://huggingface.co/datasets/callanwu/WebWalkerQA.webfaqWebFAQ Q&A Dataset
Overview |
Details |
Structure |
Examples |
Considerations |
License |
Citation |
Contact |
Acknowledgement
Overview
The WebFAQ Q&A Dataset is a broad-coverage corpus of 96 million natural question-answer (QA) pairs in 75 languages, gathered from FAQ pages on the web. It leverages structured schema.org FAQPage annotations, making it a unique resource for large-scale Question Answering… See the full description on the dataset page: https://huggingface.co/datasets/PaDaS-Lab/webfaq.WebInstruct-verified
General-Reasoner: Advancing LLM Reasoning Across All Domains
💻 Code |
📄 Paper |
📊 Dataset |
🤗 Model |
🌐 Project Page
Overview
Figure: Effectiveness of General-Reasoner trained with diverse verifiable reasoning questions using model-based verifier compared to baseline methods on various reasoning tasks.
General-Reasoner is a training paradigm for large language models (LLMs), designed to robustly enhance reasoning abilities across… See the full description on the dataset page: https://huggingface.co/datasets/TIGER-Lab/WebInstruct-verified.DLR-Web
DLR-Web: Multidisciplinary Reasoning Dataset from Web Corpus [Project Page]
This repository releases the Design-Logic-Reasoning-Web (DLR-Web) dataset from the paper DESIGNER: Design-Logic-Guided Multidisciplinary Data Synthesis for LLM Reasoning (ICLR 2026).
Field definitions
original_document: web-sourced raw document text, further filtered from FineFineWeb; thanks to the FineFineWeb authors and maintainers for providing this resource
design_logic: Design Logic in… See the full description on the dataset page: https://huggingface.co/datasets/Attention1115/DLR-Web.WebFAQRetrieval
WebFAQRetrieval
An MTEB dataset
Massive Text Embedding Benchmark
WebFAQ is a broad-coverage corpus of natural question-answer pairs in 75 languages, gathered from FAQ pages on the web.
Task category
t2t
Domains
Web, Written
Reference
https://huggingface.co/PaDaS-Lab
Source datasets:
PaDaS-Lab/webfaq-retrieval
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/WebFAQRetrieval.Edge-Agent-Reasoning-WebSearch-260K
Edge Agent Reasoning WebSearch 260K
Abstract
The Edge-Agent-Reasoning-WebSearch-260K dataset is a massive, synthetically expert-engineered corpus of over 700 Million tokens, designed to train small, local models (SLMs) and edge-deployed agents in advanced problem deconstruction and self-aware reasoning.
Rather than training a model to execute instructions directly—which often leads to hallucinations when context is missing—this dataset trains a model to act as a… See the full description on the dataset page: https://huggingface.co/datasets/BlueIsGreen/Edge-Agent-Reasoning-WebSearch-260K.Edge-Agent-Reasoning-WebSearch-260K
Edge Agent Reasoning WebSearch 260K
Abstract
The Edge-Agent-Reasoning-WebSearch-260K dataset is a massive, synthetically expert-engineered corpus of over 700 Million tokens, designed to train small, local models (SLMs) and edge-deployed agents in advanced problem deconstruction and self-aware reasoning.
Rather than training a model to execute instructions directly—which often leads to hallucinations when context is missing—this dataset trains a model to act as a… See the full description on the dataset page: https://huggingface.co/datasets/DEMIRUNC/Edge-Agent-Reasoning-WebSearch-260K.websrc
Dataset Card for WebSRC v1.0
WebSRC v1.0 is a dataset for reading comprehension on structural web pages.
The task is to answer questions about web pages, which requires a system to have a comprehensive understanding of the spatial structure and logical structure.
WebSRC consists of 6.4K web pages and 400K question-answer pairs about web pages.
This cached copy of the dataset is focused on Q&A using the web screenshots (HTML and other metadata are omitted).
Questions in WebSRC… See the full description on the dataset page: https://huggingface.co/datasets/bevaya/websrc.web-bench
Web-Bench: Unified Web Search QA Benchmarks
A curated collection of 7 web search and question-answering benchmarks in a unified format, totaling 3943 questions across 5 base datasets with reference URL variants.
📊 Dataset Overview
Dataset
Split
Records
Language
URLs Included
Description
HLE
hle
2,158
EN
❌
Multiple choice questions from Humanity's Last Exam
GAIA-text
gaia_text
103
EN
❌
Text-only GAIA benchmark (dev split)
WebWalkerQA
webwalkerqa
680
EN
❌… See the full description on the dataset page: https://huggingface.co/datasets/ZhuofengLi/web-bench.Intel-WebCorpus-forms
💻 Intel WebCorpus Forms (Enterprise Hardware Q&A)
This dataset is a massive, high-fidelity archive of 176,472 technical troubleshooting discussions (containing nearly 1 million individual messages) scraped from the official Intel Community Forums.
It has been meticulously engineered for Large Language Model (LLM) training. Instead of a raw, messy dump of isolated posts, the data has been reconstructed into chronological conversation threads, noise-filtered, deduplicated, and… See the full description on the dataset page: https://huggingface.co/datasets/sphita/Intel-WebCorpus-forms.Edge-Agent-Reasoning-WebSearch-260K
Edge Agent Reasoning WebSearch 260K
Abstract
The Edge-Agent-Reasoning-WebSearch-260K dataset is a massive, synthetically expert-engineered corpus of over 700 Million tokens, designed to train small, local models (SLMs) and edge-deployed agents in advanced problem deconstruction and self-aware reasoning.
Rather than training a model to execute instructions directly—which often leads to hallucinations when context is missing—this dataset trains a model to act as a… See the full description on the dataset page: https://huggingface.co/datasets/Torenn/Edge-Agent-Reasoning-WebSearch-260K.webglm-qa
WebGLM-QA
Dataset Description
WebGLM-QA is the dataset used to train the WebGLM generator module. It consists of 43,579 high-quality data samples for the train split, 1,000 for the validation split, and 400 for the test split. Refer to our paper for the data construction details.
Dataset Structure
To load the dataset, you can try the following code.
from datasets import load_dataset
load_dataset("THUDM/webglm-qa")
DatasetDict({
train: Dataset({… See the full description on the dataset page: https://huggingface.co/datasets/zai-org/webglm-qa.WebInstructFull
🦣 MAmmoTH2: Scaling Instructions from the Web
Project Page: https://tiger-ai-lab.github.io/MAmmoTH2/
Paper: https://arxiv.org/pdf/2405.03548
Code: https://github.com/TIGER-AI-Lab/MAmmoTH2
WebInstruct (Full)
This repo the entire dataset used in "MAmmoTH2: Scaling Instructions from the Web". The dataset is licensed under CC BY-NC 4.0, which means that the dataset can only be used for non-commercial purposes; any use that involves profit-making or commercial advantage is… See the full description on the dataset page: https://huggingface.co/datasets/TIGER-Lab/WebInstructFull.edge-agent-reasoning-websearch-260k
Edge Agent Reasoning WebSearch 260K
Abstract
The Edge-Agent-Reasoning-WebSearch-260K dataset is a massive, synthetically expert-engineered corpus of over 700 Million tokens, designed to train small, local models (SLMs) and edge-deployed agents in advanced problem deconstruction and self-aware reasoning.
Rather than training a model to execute instructions directly—which often leads to hallucinations when context is missing—this dataset trains a model to act as a… See the full description on the dataset page: https://huggingface.co/datasets/ppenner/edge-agent-reasoning-websearch-260k.securecode-web-archive
SecureCode Web: Traditional Web & Application Security Dataset
Production-grade web security vulnerability dataset with complete incident grounding, 4-turn conversational structure, and comprehensive operational guidance
Paper | GitHub | Dataset | Model Collection | Blog Post
What's new in v2.6
v2.6 restores proper Express.js coverage for the topics whose examples were removed in v2.5.1 (they had
shared one reused answer). 29 new, genuinely distinct Express.js… See the full description on the dataset page: https://huggingface.co/datasets/ChipHolmes/securecode-web-archive.WebQualityEdge-Agent-Reasoning-WebSearch-260K
Edge Agent Reasoning WebSearch 260K
Abstract
The Edge-Agent-Reasoning-WebSearch-260K dataset is a massive, synthetically expert-engineered corpus of over 700 Million tokens, designed to train small, local models (SLMs) and edge-deployed agents in advanced problem deconstruction and self-aware reasoning.
Rather than training a model to execute instructions directly—which often leads to hallucinations when context is missing—this dataset trains a model to act as a… See the full description on the dataset page: https://huggingface.co/datasets/JACKYS999/Edge-Agent-Reasoning-WebSearch-260K.Agent-Reasoning-WebSearch-260K
Edge Agent Reasoning WebSearch 260K
Abstract
The Edge-Agent-Reasoning-WebSearch-260K dataset is a massive, synthetically expert-engineered corpus of over 700 Million tokens, designed to train small, local models (SLMs) and edge-deployed agents in advanced problem deconstruction and self-aware reasoning.
Rather than training a model to execute instructions directly—which often leads to hallucinations when context is missing—this dataset trains a model to act as a… See the full description on the dataset page: https://huggingface.co/datasets/kanepi-1977/Agent-Reasoning-WebSearch-260K.Edge-Agent-Reasoning-WebSearch-260K
Edge Agent Reasoning WebSearch 260K
Abstract
The Edge-Agent-Reasoning-WebSearch-260K dataset is a massive, synthetically expert-engineered corpus of over 700 Million tokens, designed to train small, local models (SLMs) and edge-deployed agents in advanced problem deconstruction and self-aware reasoning.
Rather than training a model to execute instructions directly—which often leads to hallucinations when context is missing—this dataset trains a model to act as a… See the full description on the dataset page: https://huggingface.co/datasets/svryn/Edge-Agent-Reasoning-WebSearch-260K.Web3-Dataset
Web3Coders Smart Contracts Dataset – 2026 Edition
Version 2.0 (August 2026) – The largest curated collection of production-grade smart contracts with integrated security audits, gas profiles, vulnerability annotations, and Halal compliance tags for Shariah‑aware Web3 development.
Dataset Description
A comprehensive, multi‑chain dataset of smart contracts (Solidity, Vyper, Rust, and Move) with:
Full source code, bytecode, and ABI
Security audit outcomes (Slither… See the full description on the dataset page: https://huggingface.co/datasets/KurniaKadir/Web3-Dataset.KG-TRACES-WebQSP
KG-TRACES: Enhancing Large Language Models with Knowledge Graph-constrained Trajectory Reasoning and Attribution Supervision
This repository contains the datasets associated with the paper KG-TRACES: Enhancing Large Language Models with Knowledge Graph-constrained Trajectory Reasoning and Attribution Supervision.
Code: https://github.com/Edaizi/KG-TRACES
Abstract
Large language models (LLMs) have made remarkable strides in various natural language processing tasks… See the full description on the dataset page: https://huggingface.co/datasets/Edaizi/KG-TRACES-WebQSP.afrofinchain-multilingual-web3
AfroFinChain — Multilingual Web3 & Blockchain Dataset
Multilingual Web3 & blockchain dataset in Yoruba, Hausa, Igbo, and Nigerian Pidgin with 1,451 terminology entries and 1,451 conversational Q&A pairs. Designed for LLM fine-tuning, financial literacy, and conversational AI in low-resource African languages. Uses culturally grounded analogies (e.g., ajo, adashi, isusu) to make DeFi concepts actually understandable.
Built with Adaptive Data by Adaption as part of the Adaption… See the full description on the dataset page: https://huggingface.co/datasets/FirstBML1/afrofinchain-multilingual-web3.Vietnamese-nampdn-ai-tiny-webtext-gg-translated