datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
design-patents-not-in-impact
US Design Patents Not Included in IMPACT (2008-2026)
Original drawing images (TIFF) and grant full-text XML for 165,917 US design patents that are
absent from the AI4Patents/IMPACT dataset.
IMPACT covers 2007-2022 and contains 434,498 rows. This dataset supplies the design patents that
IMPACT does not have: 161,093 patents granted in 2023-2026, which are outside IMPACT's period,
plus 4,824 patents from years IMPACT does cover but did not include. There is no patent
overlap with… See the full description on the dataset page: https://huggingface.co/datasets/SoichiOnozuka/design-patents-not-in-impact.notch-beam-2d-impact
NotchBeam2D-Impact — StructBench canonical dataset
Download
One case, one file — fetch exactly what you need (pip install huggingface_hub):
from huggingface_hub import hf_hub_download, snapshot_download
# one case
path = hf_hub_download("StructBench/notch-beam-2d-impact",
filename="<case_id>.h5", repo_type="dataset")
# the full archive (resumable; cached under HF_HOME)
root = snapshot_download("StructBench/notch-beam-2d-impact"… See the full description on the dataset page: https://huggingface.co/datasets/StructBench/notch-beam-2d-impact.taylor-impact-2d
Taylor2D-Impact — StructBench canonical dataset
Download
One case, one file — fetch exactly what you need (pip install huggingface_hub):
from huggingface_hub import hf_hub_download, snapshot_download
# one case
path = hf_hub_download("StructBench/taylor-impact-2d",
filename="<case_id>.h5", repo_type="dataset")
# the full archive (resumable; cached under HF_HOME)
root = snapshot_download("StructBench/taylor-impact-2d", repo_type="dataset")… See the full description on the dataset page: https://huggingface.co/datasets/StructBench/taylor-impact-2d.ImplicitHate
Implicit Hate Speech
Latent Hatred: A Benchmark for Understanding Implicit Hate Speech
[Read the Paper] | [Take a Survey to Access the Data] | [Download the Data]
Why Implicit Hate?
It is important to consider the subtle tricks that many extremists use to mask their threats and abuse. These more implicit forms of hate speech may easily go undetected by keyword detection systems, and even the most advanced architectures can fail if they have not been trained on… See the full description on the dataset page: https://huggingface.co/datasets/SALT-NLP/ImplicitHate.nasa-smd-IR-benchmark
NASA-IR benchmark
NASA SMD and IBM Research developed a domain-specific information retrieval benchmark, NASA-IR, spanning almost 500 question-answer pairs related to the Earth science, planetary science, heliophysics, astrophysics, and biological physical sciences domains. Specifically, we sampled a set of 166 paragraphs from AGU, AMS, ADS, PMC, and PubMed and manually annotated with 3 questions that are answerable from each of these paragraphs, resulting in 498 questions. We used… See the full description on the dataset page: https://huggingface.co/datasets/nasa-impact/nasa-smd-IR-benchmark.implicit-hate-stg1https://github.com/SALT-NLP/implicit-hate
@inproceedings{elsherief-etal-2021-latent,
title = "Latent Hatred: A Benchmark for Understanding Implicit Hate Speech",
author = "ElSherief, Mai and
Ziems, Caleb and
Muchlinski, David and
Anupindi, Vaishnavi and
Seybolt, Jordyn and
De Choudhury, Munmun and
Yang, Diyi",
booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year =… See the full description on the dataset page: https://huggingface.co/datasets/tasksource/implicit-hate-stg1.ImpliRet
✨ Key features
Document-side reasoning: retrievers cannot rely on query expansion or multi-hop tricks— they must
understand the document.
Three reasoning types × two styles: exposes models to arithmetic, temporal and world-knowledge
inference in both conversational and forum prose.
Negatives in-pool: each query's pool contains 29 stylistically similar distractors.
🔖 Field specification
Field
Type
Present in
Description
id
string
all
Unique example id… See the full description on the dataset page: https://huggingface.co/datasets/zeinabTaghavi/ImpliRet.lab-grown-diamond-import-monitor
US Lab-Grown Diamond Import Monitor
A reproducible monthly dataset on United States imports of loose cut laboratory-grown
diamonds. The primary series uses US Census Bureau HTS 7104.91.10.00 data. UN
Comtrade HS 710491 data provides a partner-country cross-check.
The primary series covers stones cut but not set, suitable for jewelry manufacture.
It excludes diamonds imported already set in finished jewelry and rough diamonds.
It therefore does not measure total lab-grown diamond… See the full description on the dataset page: https://huggingface.co/datasets/JacobiusMakes/lab-grown-diamond-import-monitor.nasa-science-repos-sme-benchmark
NASA Science Repos SME Benchmark
A benchmark dataset for evaluating retrieval systems on NASA science repository discovery tasks. This dataset contains expert queries, a corpus of NASA science GitHub repositories, and relevance judgments.
Dataset Structure
Files
├── corpus.jsonl # 5,264 repositories with full metadata
├── queries.jsonl # 219 expert queries
└── qrels/
├── earth.tsv # Earth Science relevance judgments (162)
├──… See the full description on the dataset page: https://huggingface.co/datasets/nasa-impact/nasa-science-repos-sme-benchmark.implicaturesImplicature corpus
@article{george2020conversational,
title={Conversational implicatures in English dialogue: Annotated dataset},
author={George, Elizabeth Jasmi and Mamidi, Radhika},
journal={Procedia Computer Science},
volume={171},
pages={2316--2323},
year={2020},
publisher={Elsevier}
}
Augmented with generated distractors https://colab.research.google.com/drive/1ix0FgwzPAjQkIQA2E3ctlylvcmya7vGy?usp=sharing, for tasksource
@article{sileo2023tasksource,
title={tasksource:… See the full description on the dataset page: https://huggingface.co/datasets/tasksource/implicatures.nasa-science-code-benchmark-v0.1.1
NASA Code Retrieval Benchmark v0.1.1
This repository is an updated version of the NASA Code Retrieval Benchmark. It provides a code retrieval benchmark based on code from 7 programming languages sourced from NASA's GitHub repositories.
What's New in v0.1.1?
v0.1.1 introduces a hierarchical structure and official Hugging Face dataset configurations. This allows you to evaluate models specifically by language or by query category without data redundancy in the file system.… See the full description on the dataset page: https://huggingface.co/datasets/nasa-impact/nasa-science-code-benchmark-v0.1.1.ImplicitPersonalizationData
Implicit Personalization in Language Models: A Systematic Study
The work has been accepted to EMNLP 2024 Findings.
Abstract: Implicit Personalization (IP) is a phenomenon of language models inferring a user's background from the implicit cues in the input prompts and tailoring the response based on this inference. While previous work has touched upon various instances of this problem, there lacks a unified framework to study this behavior. This work systematically studies IP through… See the full description on the dataset page: https://huggingface.co/datasets/Jerry999/ImplicitPersonalizationData.premier-league-first-goal-impact-2025-26
What Is the First Goal Worth? — 2025/26 Premier League
Match-level data behind a 5DollarFootballAPI study of how the first confirmed goal changed
Bet365's normalized in-play win probabilities during the 2025/26 Premier League season.
Across 347 usable matches, the median within-match increase in the scoring team's normalized
win probability was 23.1 percentage points (bootstrap 95% CI: 22.4–24.2). The median
first goal after minute 75 moved the probability by 62.2 points… See the full description on the dataset page: https://huggingface.co/datasets/5dollarfootballapi/premier-league-first-goal-impact-2025-26.nasa-science-github-repos
NASA Science GitHub Repositories
A curated index of 5,264 GitHub repositories relevant to the NASA Science Mission
Directorate (SMD), spanning five science divisions: Earth Science, Astrophysics,
Planetary Science, Heliophysics, and Biological & Physical Sciences.
This dataset is designed to support research on information retrieval and
discoverability of open-source scientific software.
Licensing and Intellectual Property
This dataset is released under CC-BY-4.0 and… See the full description on the dataset page: https://huggingface.co/datasets/nasa-impact/nasa-science-github-repos.ImplicatureX
ImplicatureX
More information can be found at https://github.com/cesare-spinoso/ImplicatureX.
import pandas as pd
# skiprows=1: the first line is a leading comment, not part of the header
df = pd.read_csv("implicatureX.csv", skiprows=1)
Citation
If you use our data, please cite us:
@misc{piano2026evaluatingcommunicativebeliefupdates,
title={Evaluating Communicative Belief Updates in Large Language Models via Implicature Recognition and Cancellation}… See the full description on the dataset page: https://huggingface.co/datasets/McGill-NLP/ImplicatureX.nasa-science-code-benchmark-v0.1
NASA Code Retrieval Benchmark v0.1
Note: This dataset has been superseded by nasa-impact/nasa-science-code-benchmark-v0.1.1, which introduces a hierarchical structure, official Hugging Face dataset configurations, and evaluation by NASA science division. Please use v0.1.1 for new work.
This dataset provides a code retrieval benchmark based on code from 7 programming languages (Python, C, C++, Java, JavaScript, Fortran, and Matlab) sourced from NASA's GitHub repositories. It serves… See the full description on the dataset page: https://huggingface.co/datasets/nasa-impact/nasa-science-code-benchmark-v0.1.ImpactOfFossilFuelPrice-WACC
ImpactOfFossilFuelPrice-WACC
A compact research dataset for studying how fossil fuel price forecasts and inflation forecasts relate to the weighted average cost of capital (WACC) for energy transition projects.
The release packages cleaned regional WACC panels, forecast covariates, robustness metrics, price-shock elasticities, transmission diagnostics, and Croissant-compatible metadata.
At A Glance
Field
Value
Domain
Climate finance, energy transition… See the full description on the dataset page: https://huggingface.co/datasets/global-nomad-nexus/ImpactOfFossilFuelPrice-WACC.importe-originalwert
importe-originalwert
Unofficial Notice
This repository is a private open-source project and is not an official repository of the Federal Statistical Office of Germany (Destatis).
Data Explanation
Official dataset label: Importe, Originalwerte
Source CSV: https://www.destatis.de/static/de_/opendata/data/importe_originalwert.csv
Source page: https://www.destatis.de/EN/Service/OpenData/short-term-indicators.html
Snapshot timestamp (UTC):… See the full description on the dataset page: https://huggingface.co/datasets/destatis/importe-originalwert.impressive-service-c26cb0
impressive-service-c26cb0
Synthetic weather test data: 33 rows in data.csv.
All values are randomly generated fictional examples, not real observations, products, or user activity. Intended only for CSV loading and pipeline tests; not suitable for scientific or business conclusions. Columns are sampled independently and do not model real-world correlations.
Fields
sample_id: random identifier for this generated sample.
row_id: sequential row number starting at 1.… See the full description on the dataset page: https://huggingface.co/datasets/hayleybrown/impressive-service-c26cb0.improved-genie2-samplesIMPLICIT-Bench
IMPLICIT-Bench: Prompts
Prompts for IMPLICIT-Bench, a benchmark for measuring stereotype bias in
text-to-image (T2I) models. Each unit consists of three parallel prompts —
neutral, stereotype-trigger, and anti-stereotype-trigger — built around
a (head, relation, tail) knowledge-graph triple extracted from existing
fairness datasets. The triple structure lets you measure both whether a model
defaults to the stereotype on a neutral prompt and whether it can be
steered away from it… See the full description on the dataset page: https://huggingface.co/datasets/anonymous-research-lab/IMPLICIT-Bench.impossible-marriage-75080d
impossible-marriage-75080d
Synthetic products test data: 30 rows in data.csv.
All values are randomly generated fictional examples, not real observations, products, or user activity. Intended only for CSV loading and pipeline tests; not suitable for scientific or business conclusions. Columns are sampled independently and do not model real-world correlations.
Fields
sample_id: random identifier for this generated sample.
row_id: sequential row number starting at… See the full description on the dataset page: https://huggingface.co/datasets/Prism-Theo815/impossible-marriage-75080d.uk-home-improvement-costs
UK Home Improvement Costs 2026 (155 jobs, with regional breakdowns)
Independent guide prices for the 155 most-searched UK home-improvement jobs, from a new boiler or loft conversion to a resin driveway or double glazing, published by Costwise. Each job carries a realistic "from", "typical" and "up to" price in GBP, the pricing unit, a typical on-site timeline, and the month its figures were last reviewed, plus a regional breakdown.
Files… See the full description on the dataset page: https://huggingface.co/datasets/costwiseuk/uk-home-improvement-costs.NOAA_event_with_summary
Name: event name according to NOAA
Disaster: disaster event type according to NOAA
Begin Date: event begin date according to NOAA
End Date: event end date according to NOAA
CPI-Adjusted Cost: CPI-adjusted cost of the event according to NOAA
Unadjusted Cost: non-adjusted cost of the event according to NOAA
Deaths: deaths caused by the event according to NOAA
Event Duration: event duration according to NOAA
Event ID: ID of the event in the NOAA billion-dollar dataset
Summary: event description… See the full description on the dataset page: https://huggingface.co/datasets/extreme-weather-impacts/NOAA_event_with_summary.RSVP
📊 RSVP-X Dataset Statistics
Important Note
The dataset consists of 3,076 unique prompts, where each prompt is paired with responses across the three HHH dimensions:
Helpfulness
Harmlessness
Honesty
As a result, the final dataset contains:
3,076 Prompts × 3 Responses = 9,228 Total Samples
Table 1: Statistics Across All Four Dimensions in RSVP-X
Dimension
|X|
|~X| / |X' \ Q|
|r_i^(o)|
|F+| / |F|
|R|
Reasoning
476
827 / 145
682
520 /… See the full description on the dataset page: https://huggingface.co/datasets/impressive-east579/RSVP.import-export-tradeflex-damage-impactsimportant-explanation-b3f44c
important-explanation-b3f44c
Synthetic sensors test data: 39 rows in data.csv.
All values are randomly generated fictional examples, not real observations, products, or user activity. Intended only for CSV loading and pipeline tests; not suitable for scientific or business conclusions. Columns are sampled independently and do not model real-world correlations.
Fields
sample_id: random identifier for this generated sample.
row_id: sequential row number starting at… See the full description on the dataset page: https://huggingface.co/datasets/takahashisatomi1/important-explanation-b3f44c.spacr-example-import
spaCR — Import test data
The same four microscope fields written in every container format and filename convention the Import module of spaCR reads, each with its cell, nucleus and pathogen masks and the measurements of its cells. It is the data behind Load test data… on the Import screen: pick a variant, and spaCR fills the screen with it and previews the import, so you can see every file land on the well, field and channel it came from.
About 283 MB in one uncompressed archive… See the full description on the dataset page: https://huggingface.co/datasets/einarolafsson/spacr-example-import.africa-imports-of-goods-and-services-percentage-of-gdp
Africa Imports of Goods and Services Percentage of Gdp | Africa (World Bank)
Size category: n<1K - Formats: csv - Sector: economics_finance - 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
Public datasets help analysts… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-imports-of-goods-and-services-percentage-of-gdp.