datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
WebLINX-full
WebLINX: Real-World Website Navigation with Multi-Turn Dialogue
WARNING: This is not the main WebLINX data card! You might want to use the main WebLINX data card instead:
WebLINX: Real-World Website Navigation with Multi-Turn Dialogue
WebLINX: Real-World Website Navigation with Multi-Turn Dialogue
Xing Han Lù*, Zdeněk Kasner*, Siva Reddy
💾Code
📄Paper
🌐Website
📓Colab
🤖Models
💻Explorer
🐦Tweets
🏆Leaderboard
Your browser does not support the… See the full description on the dataset page: https://huggingface.co/datasets/McGill-NLP/WebLINX-full.yelp_review_full
Dataset Card for YelpReviewFull
Dataset Summary
The Yelp reviews dataset consists of reviews from Yelp.
It is extracted from the Yelp Dataset Challenge 2015 data.
Supported Tasks and Leaderboards
text-classification, sentiment-classification: The dataset is mainly used for text classification: given the text, predict the sentiment.
Languages
The reviews were mainly written in english.
Dataset Structure
Data Instances
A… See the full description on the dataset page: https://huggingface.co/datasets/Yelp/yelp_review_full.s2orc_full
S2ORC Full — Semantic Scholar Open Research Corpus
A complete redistribution of the S2ORC dataset in Parquet format on Hugging Face, containing 14.5 million academic papers with full text, structured metadata, and citation information.
Dataset Description
S2ORC (Semantic Scholar Open Research Corpus) is a general-purpose corpus for NLP and text mining research over scientific papers, originally developed by the Allen Institute for AI. This version provides the full… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicResearchGroup/s2orc_full.pd12m-fullThis dataset is the downloaded variant of Spawning/PD12M. More specifically, this dataset
is compatible with webdataset. It was made public after obtaining permission
from the original authors of the dataset.
You can use the following to explore the dataset with webdataset:
import webdataset as wds
dataset_path = "pipe:curl -s -f -L https://huggingface.co/datasets/sayakpaul/pd12m-full/resolve/main/{00155..02480}.tar"
dataset = (
wds.WebDataset(dataset_path… See the full description on the dataset page: https://huggingface.co/datasets/Spawning/pd12m-full.vsi-bench-qa-v3-hm3d-fullPromptEval_MMLU_full
MMLU Multi-Prompt Evaluation Data
Overview
This dataset contains the results of a comprehensive evaluation of various Large Language Models (LLMs) using multiple prompt templates on the Massive Multitask Language Understanding (MMLU) benchmark. The data is introduced in
Maia Polo, Felipe, Ronald Xu, Lucas Weber, Mírian Silva, Onkar Bhardwaj, Leshem Choshen, Allysson Flavio Melo de Oliveira, Yuekai Sun, and Mikhail Yurochkin. "Efficient multi-prompt evaluation of LLMs."… See the full description on the dataset page: https://huggingface.co/datasets/PromptEval/PromptEval_MMLU_full.aitw-processed-labeled-full
AiTW Processed Full with App Labels
This repository contains a full processed Android in the Wild (AiTW) mirror together with an app-labeled step index, official split assignment by episode_id, major-app statistics, and a ready-to-train Gmail subset.
Why This Exists
AiTW is large and not easy to navigate by app. The original labels contain useful fields such as goal_info, current_activity, and action coordinates, but users often need extra processing before they… See the full description on the dataset page: https://huggingface.co/datasets/KMK040412/aitw-processed-labeled-full.banana-vidorev3-fullpipe
Banana ViDoRe v3 Fullpipe
Nano Banana Pro full-pipeline synthetic training data for ViDoRe v3 finance and industrial domains.
This repository contains 4670 training records and 40190 unique referenced images across
domain-separated ColFlor/ColQwen training splits. Images are included in the repository and paths in each JSONL are
relative to that domain directory.
Generated at: 2026-06-29T09:39:01.644860+00:00
Layout
finance/train.jsonl
finance/metadata.json… See the full description on the dataset page: https://huggingface.co/datasets/vkehfdl1/banana-vidorev3-fullpipe.financial-analyst-data-full
financial-analyst-data-full
A-share historical price + valuation data packaged for financial-analyst —
the 14-agent single-stock deep-dive research workstation.
Published: 2026-05-24
Preset: full — 全 A 股完整包 (含历史退市股). 量化研究员 / 重度用户. lite 全 + TDX 历年财报原始 zip (用户跑 import_tdx_financial.py 解) + F10 原始文本 (公司大事/龙虎榜/主力追踪/最新提示 .txt).
Size: ~14.1 GB
What's included
5450 stocks daily OHLCV + 7 valuation fields (PE/PB/PS/DV/MV/CIRC_MV/turnover_rate)
Date range (daily): 1990-12-19… See the full description on the dataset page: https://huggingface.co/datasets/yifishbossman/financial-analyst-data-full.icrm-hitek-full-db-mixed
ICMR + HITEK Full DB (Mixed) — Prebuilt Indexes + One-Click Setup
Prebuilt sorted indexes for the Kzr0xx/Icmr-and-hitek dataset (2.5B rows, 11 columns, ~104 GB raw parquet).
Building these indexes took ~17 hours of compute. This repo saves you that work: download + run = API live in ~1-2 hours (download speed dependent).
Contents
The indexes are stored as sorted parts (each < 50 GB, split at row-group boundaries, order preserved) because HuggingFace's classic HTTP… See the full description on the dataset page: https://huggingface.co/datasets/MRSHREY197/icrm-hitek-full-db-mixed.MMFineReason-Full-2.3M-Qwen3-VL-235B-Thinking
MMFineReason-Full-2.3M
The Complete Pre-Selection Dataset — Before Quality Filtering
📖 Overview
MMFineReason-Full-2.3M is the complete pre-selection dataset containing 2.3M samples and 8.8B solution tokens, generated through our reasoning distillation pipeline before the data selection stage. This dataset includes all samples that passed basic template and length validation, but have not undergone correctness verification filtering.
🎯 Key Characteristics… See the full description on the dataset page: https://huggingface.co/datasets/OpenDataArena/MMFineReason-Full-2.3M-Qwen3-VL-235B-Thinking.sat-image-boundingbox-sft-full
NU-TONIC raw SFT Full
Satellite imagery and aligned land-cover outputs packaged as image–text rows for fine-tuning in SFT format. JSONL user prompts name the modality (satellite imagery vs. overhead context) where it matters.
Provenance
Locations: GeoGuessr-style POIs (source: stochastic/random_streetview_images_pano_v0.0.2)
Optical: Sentinel-2 multispectral optical COGs from a public STAC catalog, blue/green/red or visual preview, percentile-stretched to uint8.
Labels:… See the full description on the dataset page: https://huggingface.co/datasets/NuTonic/sat-image-boundingbox-sft-full.migration-bench-java-full
MigrationBench
1. 📖 Overview
🤗 MigrationBench
is a large-scale code migration benchmark dataset at the repository level,
across multiple programming languages.
Current and initial release includes java 8 repositories with the maven build system… See the full description on the dataset page: https://huggingface.co/datasets/AmazonScience/migration-bench-java-full.ICMR-HITEK-FULL-MIXED-DB
ICMR + HITEK Full DB (Mixed) — Prebuilt Indexes + One-Click Setup
Prebuilt sorted indexes for the Kzr0xx/Icmr-and-hitek dataset (2.5B rows, 11 columns, ~104 GB raw parquet).
Building these indexes took ~17 hours of compute. This repo saves you that work: download + run = API live in ~1-2 hours (download speed dependent).
Contents
The indexes are stored as sorted parts (each < 50 GB, split at row-group boundaries, order preserved) because HuggingFace's classic HTTP… See the full description on the dataset page: https://huggingface.co/datasets/devil-69/ICMR-HITEK-FULL-MIXED-DB.free-music-archive-full
FMA: A Dataset for Music Analysis
Michaël Defferrard, Kirell Benzi, Pierre Vandergheynst, Xavier Bresson.
International Society for Music Information Retrieval Conference (ISMIR), 2017.
We introduce the Free Music Archive (FMA), an open and easily accessible dataset suitable for evaluating several tasks in MIR, a field concerned with browsing, searching, and organizing large music collections. The community's growing interest in feature and end-to-end learning is however restrained… See the full description on the dataset page: https://huggingface.co/datasets/benjamin-paine/free-music-archive-full.wikipedia-bge-small-en-v1.5-fullicrm-hitek-fulldbbeamit-full-texts-dataset
Dataset Card for "beamit-full-texts-dataset"
More Information needed
3D_full_poly_genpreprocessed_DCAE-f64_1024_pd12m-full3D_full_poly_rot_genicrm-hitek-fulldbarvo-vulnsmith-full
ARVO CyberGym-format smoke dataset
This dataset is shaped to be loaded by Harbor's CyberGym adapter.
It contains 10 ARVO tasks that are outside the original CyberGym set.
s2orc_full
S2ORC Full — Semantic Scholar Open Research Corpus
A complete redistribution of the S2ORC dataset in Parquet format on Hugging Face, containing 14.5 million academic papers with full text, structured metadata, and citation information.
Dataset Description
S2ORC (Semantic Scholar Open Research Corpus) is a general-purpose corpus for NLP and text mining research over scientific papers, originally developed by the Allen Institute for AI. This version provides the full… See the full description on the dataset page: https://huggingface.co/datasets/jedibear/s2orc_full.FullBenchfreesound-laion-640k-commercial-16khz-full
About this Repository
This repository is the training split of the complete FreeSound LAION 640k dataset, limited only to licenses that permit commercial works, resampled to 16khz using torchaudio.transforms.Resample.
This is ideal for use cases where a variety of audio is desired but fidelity and labels are unnecessary, such as background audio for augmenting other datasets.
Dataset Versions
You are looking at the full dataset which contains 403,146 unique sounds… See the full description on the dataset page: https://huggingface.co/datasets/benjamin-paine/freesound-laion-640k-commercial-16khz-full.full_checkbox_dropdown_radiobuttonDatBench-Full
DatBench: Discriminative, Faithful, and Efficient VLM Evaluations
DatBench is a curated evaluation suite for vision–language models (VLMs) designed to be faithful, discriminative, and efficient.
📄 DatBench: Discriminative, Faithful, and Efficient VLM Evaluationshttps://arxiv.org/abs/2601.02316
Modern VLM benchmarks often overestimate model capability due to multiple-choice inflation, language-only shortcuts, annotation noise, and redundant low-signal samples. DatBench reframes… See the full description on the dataset page: https://huggingface.co/datasets/DatologyAI/DatBench-Full.Birds_of_North_America_Fullfull-o46