datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
resumes
Dataset Card for Resume Dataset
Dataset Summary
Context
A collection of Resume Examples taken from livecareer.com for categorizing a given resume into any of the labels defined in the dataset.
Content
Contains 2400+ Resumes in string as well as PDF format.
PDF stored in the data folder differentiated into their respective labels as folders with each resume residing inside the folder in pdf form with filename as the id defined in the csv.
Inside the… See the full description on the dataset page: https://huggingface.co/datasets/opensporks/resumes.open-asr-leaderboard-resultsargument_quality_ranking_30k
Dataset Card for Argument-Quality-Ranking-30k Dataset
Dataset Summary
Argument Quality Ranking
The dataset contains 30,497 crowd-sourced arguments for 71 debatable topics labeled for quality and stance, split into train, validation and test sets.
The dataset was originally published as part of our paper: A Large-scale Dataset for Argument Quality Ranking: Construction and Analysis.
Argument Topic
This subset contains 9,487 of the arguments only with… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/argument_quality_ranking_30k.enabling-independent-research
Overview
This directory contains the Anthropic Insights data we provided to our three external research groups as part of the collaboration detailed in "Enabling independent research on how people use Claude".
Before using this data, we recommend first reading our blog post on this collaboration and the Anthropic Insights paper and blog post. Before drawing conclusions from this data — especially from open-ended clusters — please read "Guidance for Interpreting Open-Ended… See the full description on the dataset page: https://huggingface.co/datasets/Anthropic/enabling-independent-research.resume-job-description-fitSpatialLM-Testset
SpatialLM Testset
Project page | Paper | Code
We provide a test set of 107 preprocessed point clouds and their corresponding GT layouts, point clouds are reconstructed from RGB videos using MASt3R-SLAM. SpatialLM-Testset is quite challenging compared to prior clean RGBD scan datasets due to the noises and occlusions in the point clouds reconstructed from monocular RGB videos.
Folder Structure
Outlines of the dataset files:… See the full description on the dataset page: https://huggingface.co/datasets/manycore-research/SpatialLM-Testset.Customer-Support-ResponsesE2AM_ResNet50
E2AM Ablation Results: ResNet-50
Energy-aware training ablation study for ResNet-50 across three image-classification datasets: CIFAR-10, CIFAR-100, and Tiny-ImageNet.
Each dataset has 15 training variants (8 individual-method M0..M7, 7 cumulative ablation C0..C6) at 50 epochs, plus a 5-variant deployment pipeline (FP32 baseline, structured pruning, pruning+finetune, INT8 quantization, pruned+INT8).
Status: 45 completed variants, 0 partial.
Quick links… See the full description on the dataset page: https://huggingface.co/datasets/Shanmuk4622/E2AM_ResNet50.SPML_Chatbot_Prompt_Injection
SPML Chatbot Prompt Injection Dataset
Arxiv Paper
Introducing the SPML Chatbot Prompt Injection Dataset: a robust collection of system prompts designed to create realistic chatbot interactions, coupled with a diverse array of annotated user prompts that attempt to carry out prompt injection attacks. While other datasets in this domain have centered on less practical chatbot scenarios or have limited themselves to "jailbreaking" – just one aspect of prompt injection – our dataset… See the full description on the dataset page: https://huggingface.co/datasets/reshabhs/SPML_Chatbot_Prompt_Injection.zomato-restaurant-recommendationEnvironment-and-Natural-Resources-Indicators-For-African-Countries
Environment and Natural Resources Indicators For African Countries | Africa (World Health Organization)
Size category: 1K<n<10K - Formats: csv - Sector: climate_environment - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/Environment-and-Natural-Resources-Indicators-For-African-Countries.SpatialLM-Dataset
SpatialLM Dataset
The SpatialLM dataset is a large-scale, high-quality synthetic dataset designed by professional 3D designers and used for real-world production. It contains point clouds from 12,328 diverse indoor scenes comprising 54,778 rooms, each paired with rich ground-truth 3D annotations. SpatialLM dataset provides an additional valuable resource for advancing research in indoor scene understanding, 3D perception, and… See the full description on the dataset page: https://huggingface.co/datasets/manycore-research/SpatialLM-Dataset.Wikipedia_contradict_benchmark
Wikipedia contradict benchmark
Wikipedia contradict benchmark is a dataset consisting of 253 high-quality, human-annotated instances designed to assess LLM performance when augmented with retrieved passages containing real-world knowledge conflicts. The dataset was created intentionally with that task in mind, focusing on a benchmark consisting of high-quality, human-annotated instances.
Dataset Details
Dataset Description… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/Wikipedia_contradict_benchmark.claim_stance
Dataset Card for Claim Stance Dataset
Dataset Summary
Claim Stance
This dataset contains 2,394 labeled Wikipedia claims for 55 topics. The dataset includes the stance (Pro/Con) of each claim towards the topic,
as well as fine-grained annotations, based on the semantic model of Stance Classification of Context-Dependent Claims (topic target,
topic sentiment towards its target, claim target, claim sentiment towards its target, and the relation between the… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/claim_stance.geoparser-benchmark-results
Geoparser benchmark results
Geoparsing pipelines from geoparser scored on English and
multilingual corpora, run on Grid'5000 (one Tesla T4).
Benchmarks
Benchmark
Languages
Docs
Toponyms
Source
GeoVirus
en
229
2167
WikiNews articles on epidemics (Gritta et al., 2018).
HIPE-2020
de, en, fr
129
1516
Historical Swiss, Luxembourgish and American newspapers, OCR.
NewsEye
de, fi, fr, sv
77
1772
Historical European newspapers, OCR (HIPE-2022).
TopRes19th… See the full description on the dataset page: https://huggingface.co/datasets/NoeFlandre/geoparser-benchmark-results.taiwan-ly-law-research
Taiwan Legislator Yuan Law Research Data
Overview
The law research documents are issued irregularly from Taiwan Legislator Yuan.
The purpose of those research are providing better understanding on social issues in aspect of laws.
One may find documents rich with technical terms which could provided as training data.
For comprehensive document list check out this link provided by Taiwan Legislator Yuan.
There are currently missing document download links in 10th and 9th… See the full description on the dataset page: https://huggingface.co/datasets/aigrant/taiwan-ly-law-research.ising-sim2real-results
Ising sim2real — Decoder Benchmark Results
Evaluation results for a panel of open surface-code decoders run on real Google
Willow hardware data and on synthetic circuit-level noise of rising fidelity.
The question these results answer: does the cheap synthetic benchmark predict the
real-hardware result?
This repo holds the outputs (LERs, per-shot outcomes, fitted noise models,
figures). The inputs — ingested Willow detection events, circuits, and shipped
DEMs — live in… See the full description on the dataset page: https://huggingface.co/datasets/ShayManor/ising-sim2real-results.llava-15-rlmpq-vlm-eval-results
RL-MPQ VLM Evaluation Artifacts
Complete figures, tables, galleries, and raw benchmark CSVs for the extended VLM evaluation.
Dataset: AvoCahDoe/llava-15-rlmpq-vlm-eval-results
Collections (by base VLM)
RL-MPQ VLM — LLaVA-1.5-13B — HF collection
RL-MPQ VLM — LLaVA-1.5-7B — HF collection
RL-MPQ VLM — LLaVA-Next Mistral-7B — HF collection
RL-MPQ VLM — Qwen2-VL-7B — HF collection
Model repos
RL-MPQ High Fidelity →… See the full description on the dataset page: https://huggingface.co/datasets/AvoCahDoe/llava-15-rlmpq-vlm-eval-results.fantastic_bugs_resultmac-app-store-apps-metadata
Dataset Card for Macappstore Applications Metadata
📌 Dataset status: static snapshot (no scheduled updates). The data was collected from the public iTunes Search API between December 2023 and January 2024 and reflects the Mac App Store as of that period. The dataset is stable and remains available for research use; it is not refreshed on a schedule.
Mac App Store Applications Metadata sourced by the public API.
Curated by: MacPaw Way Ltd.
Language(s) (NLP): Mostly EN, DE… See the full description on the dataset page: https://huggingface.co/datasets/macpaw-research/mac-app-store-apps-metadata.cdl-devai-results-ds006239
ds006239 (Wang et al. 2025) — brain × interpretability × localisation, per model per checkpoint
Wang et al. 2025 — word-level phonological and semantic reading in children and adolescents. Cohort: children and adolescents 10–17 years; presentation: visual (reading).
Tasks Orth, Phon, Sem, SemLocal × sessions ses-11, ses-11+ = 8 task × session cells,
all of them scored here.
Duplicate cells. Phon/ses-11+ is bit-identical to Orth/ses-11+, Phon/ses-11 is bit-identical to… See the full description on the dataset page: https://huggingface.co/datasets/BrainAlign/cdl-devai-results-ds006239.AttaQ
AttaQ Dataset Card
The AttaQ red teaming dataset, consisting of 1402 carefully crafted adversarial questions, is designed to evaluate Large Language Models (LLMs) by assessing their tendency to generate harmful or undesirable responses.
It may serve as a benchmark to assess the potential harm of responses produced by LLMs.
The dataset is categorized into seven distinct classes of questions: deception, discrimination, harmful information, substance abuse, sexual content, personally… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/AttaQ.cdl-devai-results-ds002236
ds002236 (Lytle et al. 2020) — brain × interpretability × localisation, per model per checkpoint
Lytle et al. 2020 — orthographic, phonological and semantic word processing in school-aged children. Cohort: children 8.7–15.5 years; presentation: auditory and visual word presentation.
Tasks Phon, Sem × sessions ses-9, ses-11, ses-11+ = 6 task × session cells,
all of them scored here.
Incomplete families --- do not read these as scale-ladder points. pythia-2.8b-full has 4… See the full description on the dataset page: https://huggingface.co/datasets/BrainAlign/cdl-devai-results-ds002236.cdl-devai-results-ds003604-roiauditory
ds003604 (Wang et al. 2022) — brain × interpretability × localisation, per model per checkpoint
Wang et al. 2022 — auditory language comprehension in children. Cohort: children scanned at 5, 7 and 9; presentation: auditory.
Tasks Sem, Phon, Gram, Plaus × sessions ses-5, ses-7, ses-9 = 12 task × session cells,
all of them scored here.
Incomplete families --- do not read these as scale-ladder points. pythia-2.8b-full has 4 checkpoints, pythia-6.9b-full has 1 checkpoint.… See the full description on the dataset page: https://huggingface.co/datasets/BrainAlign/cdl-devai-results-ds003604-roiauditory.saas-vendor-outage-duration-incident-resolution-time-mttr
How long do SaaS vendor outages last? Incident resolution time per vendor, rebuilt daily
As of 2026-09-24 12:28 UTC. For every incident a vendor posted on its own public status
page with BOTH an opened time and a resolved time, this dataset computes
duration_minutes = resolved_at - started_at
and rolls it up per vendor. It is derived, every day, from the incident table in
saas-vendor-status-pages-outages-incidents-daily; the two are rebuilt by the same job and cannot
disagree.… See the full description on the dataset page: https://huggingface.co/datasets/APProjects/saas-vendor-outage-duration-incident-resolution-time-mttr.us-restaurant-hotel-closings-layoffs-warn-act-notices-daily
US restaurant and hotel closings and layoffs — the actual WARN Act filings, rebuilt every day
Last rebuilt: 2026-09-24. 6,348 layoff and closure notices filed by
restaurants and restaurant groups, hotels, motels and resorts, casinos and gaming floors, caterers and contract food-service operators, bars and coffee chains, stadium, arena and airport concessions, and leisure and entertainment venues with US state labor departments — 920,524 workers,
3,060 employers, 48 states… See the full description on the dataset page: https://huggingface.co/datasets/APProjects/us-restaurant-hotel-closings-layoffs-warn-act-notices-daily.cdl-devai-results-ds003604-roiphonology
ds003604 (Wang et al. 2022) — brain × interpretability × localisation, per model per checkpoint
Wang et al. 2022 — auditory language comprehension in children. Cohort: children scanned at 5, 7 and 9; presentation: auditory.
Tasks Sem, Phon, Gram, Plaus × sessions ses-5, ses-7, ses-9 = 12 task × session cells,
all of them scored here.
Incomplete families --- do not read these as scale-ladder points. pythia-2.8b-full has 4 checkpoints. pythia-6.9b-full's single checkpoint is step… See the full description on the dataset page: https://huggingface.co/datasets/BrainAlign/cdl-devai-results-ds003604-roiphonology.cdl-devai-results-ds003604-roimotor
ds003604 (Wang et al. 2022) — brain × interpretability × localisation, per model per checkpoint
Wang et al. 2022 — auditory language comprehension in children. Cohort: children scanned at 5, 7 and 9; presentation: auditory.
Tasks Sem, Phon, Gram, Plaus × sessions ses-5, ses-7, ses-9 = 12 task × session cells,
all of them scored here.
Incomplete families --- do not read these as scale-ladder points. pythia-2.8b-full has 4 checkpoints. pythia-6.9b-full's single checkpoint is step… See the full description on the dataset page: https://huggingface.co/datasets/BrainAlign/cdl-devai-results-ds003604-roimotor.cdl-devai-results-ds003604
ds003604 (Wang et al. 2022) — brain × interpretability × localisation, per model per checkpoint
Wang et al. 2022 — auditory language comprehension in children. Cohort: children scanned at 5, 7 and 9; presentation: auditory.
Tasks Sem, Phon, Gram, Plaus × sessions ses-5, ses-7, ses-9 = 12 task × session cells,
all of them scored here.
Incomplete families --- do not read these as scale-ladder points. pythia-2.8b-full has 4 checkpoints, pythia-6.9b-full has 1 checkpoint.… See the full description on the dataset page: https://huggingface.co/datasets/BrainAlign/cdl-devai-results-ds003604.resume-atlasPlease see paper & code for more information:
https://github.com/noran-mohamed/Resume-Classification-Dataset
https://arxiv.org/abs/2406.18125