datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SID_Set
Dataset Card for SID_Set
Dataset Summary
We provide Social media Image Detection dataSet (SID-Set), which offers three key advantages:
Extensive volume: Featuring 300K AI-generated/tampered and authentic images with comprehensive annotations.
Broad diversity: Encompassing fully synthetic and tampered images across various classes.
Elevated realism: Including images that are predominantly indistinguishable from genuine ones through mere visual inspection.
Please check… See the full description on the dataset page: https://huggingface.co/datasets/saberzl/SID_Set.colpali_train_set
Dataset Description
This dataset is the training set of ColPali it includes 127,460 query-image pairs from both openly available academic datasets (63%) and a synthetic dataset made up
of pages from web-crawled PDF documents and augmented with VLM-generated (Claude-3 Sonnet) pseudo-questions (37%).
Our training set is fully English by design, enabling us to study zero-shot generalization to non-English languages.
Dataset
#examples (query-page pairs)
Language
DocVQA
39… See the full description on the dataset page: https://huggingface.co/datasets/vidore/colpali_train_set.So-Fake-Set
Dataset Card for So-Fake-Set
Dataset Summary
We provide So-Fake-Set, A large-scale, diverse dataset tailored for social media image forgery detection!
Please check our website to explore more visual results.
Dataset Structure
"image" (Image): Input images, including real, full_synthetic, and tampered images.
"mask" (Image): Binary mask highlighting manipulated regions in tampered images.
"label" (str): Classification category.
"generator" (str): The… See the full description on the dataset page: https://huggingface.co/datasets/saberzl/So-Fake-Set.AIME_Problem_Set_1983-2024setimes
Dataset Card for SETimes – A Parallel Corpus of English and South-East European Languages
Dataset Summary
[More Information Needed]
Supported Tasks and Leaderboards
[More Information Needed]
Languages
[More Information Needed]
Dataset Structure
Data Instances
Here are some examples of questions and facts:
Data Fields
[More Information Needed]
Data Splits
[More Information Needed]
Dataset Creation… See the full description on the dataset page: https://huggingface.co/datasets/community-datasets/setimes.preference-test-sets
Preference Test Sets
Very few preference datasets have heldout test sets for validation of reward model accuracy results.
In this dataset, we curate the test sets from popular preference datasets into a common schema for easy loading and evaluation.
Anthropic HH (Helpful & Harmless Agent and Red Teaming), test set in full is 8552 samples
Anthropic HHH Alignment (Helpful, Honest, & Harmless), formatted from Big Bench for standalone evaluation.
Learning to summarize, downsampled from… See the full description on the dataset page: https://huggingface.co/datasets/allenai/preference-test-sets.Omni-Fake-SET
Omni-Fake-SET
Omni-Fake-SET is the in-distribution split of Omni-Fake, a unified multimodal deepfake dataset for social-media forensics. It covers image, audio, video, and audio–video talking-head (AV-TH) modalities. Each modality uses the same three-way label space: real, fully synthetic, and tampered. Pair with the held-out benchmark Omni-Fake-OOD for out-of-distribution evaluation.
Paper: arXiv:2605.01638
Project page: Omni-Fake
License: CC-BY-4.0
Video (hybrid… See the full description on the dataset page: https://huggingface.co/datasets/JamalLee/Omni-Fake-SET.diffusion-pretrain-set-ft1
diffusion-pretrain-set-ft1
A multi-source image-caption pretraining dataset assembled from ten upstream
sources via a uniform ingest pipeline. Designed for a full pretrain or finetune
pipeline meant to curate for any major diffusion model preliminary, with the sole
intent to create a more powerful baseline preliminary train and a baseline
for synthesizing images to train the next generation of the VLM model.
This is a lot like the snake eating it's own tail, so it must be… See the full description on the dataset page: https://huggingface.co/datasets/AbstractPhil/diffusion-pretrain-set-ft1.tweet_eval_stance_abortionOmni-Sets
Omni-Sets
A large-scale, multi-modal instruction-tuning dataset spanning six modalities (audio, speech, image, video, visual documents, and cross-modal omni) with both single-turn dense captions and multi-turn instruction-following conversations. Designed for training omni-modal language models that can perceive and reason across all modalities.
590,858 total samples | 5,635 hours of audio/video | 6 configs | 17 source datasets
Overview
Config
Modality… See the full description on the dataset page: https://huggingface.co/datasets/MBZUAI/Omni-Sets.SCOPE-OOD-set
SCOPE-60K-OOD: Out-of-Distribution LLM Routing Dataset
Dataset Description
SCOPE-60K-OOD is an out-of-distribution (OOD) evaluation dataset for LLM routing systems. It contains evaluation results from 5 frontier language models that were not seen during training, designed to test the generalization capabilities of routing methods.
Authors
Qi Cao - UC San Diego, PXie Lab
Shuhao Zhang - UC San Diego, PXie Lab
Affiliation
University of California, San… See the full description on the dataset page: https://huggingface.co/datasets/Cooolder/SCOPE-OOD-set.diffbir-mixed-setsdiffusion-pretrain-set-ft1-1024
diffusion-pretrain-set-ft1-1024
1024px (2x) upscale of AbstractPhil/diffusion-pretrain-set-ft1.
WARNING
MUCH OF THIS DATA WAS MODEL UPSCALED USING RAPID UPSCALERS.
THIS IS NOT CONSISTENTLY HIGH FIDELITY NOR IS IT EVEN CLOSE TO FAIR FIDELITY AT TIMES.
PLEASE use this ONLY for pretraining, new concepts, and simple design purposes ONLY. HEAVILY PRUNE FOR FINETUNING.
Thank you, good luck my friends.
Details
Model: realesr-general-x4v3 (SRVGG Compact… See the full description on the dataset page: https://huggingface.co/datasets/AbstractPhil/diffusion-pretrain-set-ft1-1024.banking_sentiment_setfit
Dataset Card for "banking_sentiment_setfit"
More Information needed
aihub-464-preprocessed-680GB-set-52Instruction_filtered_set
Dataset Card for "Instruction_filtered_set"
More Information needed
gutenberg_setlebanese_aug_setSID_Set
Dataset Card for SID_Set
Dataset Summary
We provide Social media Image Detection dataSet (SID-Set), which offers three key advantages:
Extensive volume: Featuring 300K AI-generated/tampered and authentic images with comprehensive annotations.
Broad diversity: Encompassing fully synthetic and tampered images across various classes.
Elevated realism: Including images that are predominantly indistinguishable from genuine ones through mere visual inspection.
Please… See the full description on the dataset page: https://huggingface.co/datasets/RAID-techjam/SID_Set.emu_edit_test_set
Dataset Card for the Emu Edit Test Set
Dataset Summary
To create a benchmark for image editing we first define seven different categories of potential image editing operations: background alteration (background), comprehensive image changes (global), style alteration (style), object removal (remove), object addition (add), localized modifications (local), and color/texture alterations (texture).
Then, we utilize the diverse set of input images from the MagicBrush… See the full description on the dataset page: https://huggingface.co/datasets/facebook/emu_edit_test_set.R1_Lite_tea_service_table_setting
R1_Lite_tea_service_table_setting
📋 Overview
This dataset uses an extended format based on LeRobot and is fully compatible with LeRobot.
Robot Type: galaxea_r1_lite
| Codebase Version: v2.1
End-Effector Type: two_finger_gripper
🏠 Scene Types
This dataset covers the following scene types:
home
🤖 Atomic Actions
This dataset includes the following atomic actions:
grasp
pick
place
📊 Dataset Statistics
Metric… See the full description on the dataset page: https://huggingface.co/datasets/RoboCOIN/R1_Lite_tea_service_table_setting.So-Fake-Set-Resized-224SID_Set
Dataset Card for SID_Set
Dataset Summary
We provide Social media Image Detection dataSet (SID-Set), which offers three key advantages:
Extensive volume: Featuring 300K AI-generated/tampered and authentic images with comprehensive annotations.
Broad diversity: Encompassing fully synthetic and tampered images across various classes.
Elevated realism: Including images that are predominantly indistinguishable from genuine ones through mere visual inspection.
Please… See the full description on the dataset page: https://huggingface.co/datasets/Beastarz/SID_Set.colpali_train_set_split_by_sourcecleangov-local-settlements
지방재정365 결산 통계 Open API (세입·세출결산, 재무제표, 지방세, 지역통합재정통계, 공공시설·청사·채무)
지방재정365 재정데이터개방 허브의 "결산" 분류 33 서비스. 세출결산(기능별·성질별·회계별·구조별 단체별), 세입결산(재원별·성질별), 기금결산, 교육비특별회계 결산, 투자적경비 순계, 재무제표(재정상태표·통합재정운영표·순자산변동표·복식부기 수익·비용·자산·부채), 지방세(징수율·세목별 비중·세수신장률·체납 누계), 지역통합재정통계 (세입·세출·자산·부채·인건비·업무추진비·행사경비 비율), 공공시설운영현황, 청사면적, 채무현황. 자치단체 재정의 결산 기준 정본이며 FISCAL-LOC-002(세부사업별 세출 XLSX) 보다 집계 수준이 높고 분류 축이 다양하다. 비교군·기관 개요 화면의 결산 수치를 여기서 낸다.
출처: https://www.lofin365.go.kr/portal/LF5100000.do
이용 조건: 허브 명세 이용조건… See the full description on the dataset page: https://huggingface.co/datasets/eddmpython/cleangov-local-settlements.aihub-464-preprocessed-680GB-set-53aihub-464-preprocessed-680GB-set-56Meta_STT_HI_Set1
Meta Speech Recognition Hindi Dataset (Set 1)
This dataset contains both metadata and audio files for Hindi speech recognition samples, curated from multiple sources.
Dataset Sources and Credits
This dataset combines samples from the following sources:
AI4Bharat Indic Speech Dataset
Source: https://ai4bharat.org/indic-speech-dataset
License: CC-BY 4.0
Citation: Please cite the original paper if you use this data
Common Voice Hindi
Source:… See the full description on the dataset page: https://huggingface.co/datasets/WhissleAI/Meta_STT_HI_Set1.bing_coronavirus_query_set
Dataset Card for BingCoronavirusQuerySet
Dataset Summary
Please note that you can specify the start and end date of the data. You can get start and end dates from here: https://github.com/microsoft/BingCoronavirusQuerySet/tree/master/data/2020
example:
load_dataset("bing_coronavirus_query_set", queries_by="state", start_date="2020-09-01", end_date="2020-09-30")
You can also load the data by country by using queries_by="country".
Supported Tasks and… See the full description on the dataset page: https://huggingface.co/datasets/microsoft/bing_coronavirus_query_set.aihub-464-preprocessed-680GB-set-57