datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Underwater-Acoustic-Channel-Repository
Underwater Acoustic Channel Repository
This Hugging Face dataset is a structured, checksum-preserving mirror of version 1.0 of the Underwater Acoustic Channel Repository. The original dataset was published by Zhengnan Li, Mandar Chitre, Diego Cuji, James Preisig, Andrew Singer, Milica Stojanovic, and Paul van Walree.
The collection contains measured underwater acoustic channel impulse responses (CIRs) from eight at-sea experimental groups. Channel and accompanying noise files… See the full description on the dataset page: https://huggingface.co/datasets/UWA-CP/Underwater-Acoustic-Channel-Repository.undominated-ai-model-pricing
Undominated AI model pricing and Arena scores
Snapshot of 437 model listings from 52 providers, measured 2026-09-23.
Every row carries its own source URL and fetch date.
Produced by https://undominated.ai · scripts/build-export.mjs
What is in here
Rows
437
Providers
52
Rows with a price
432
Rows priced at zero
23
Rows with context-tiered pricing
69
Rows with time-of-day pricing
4
Open-weight rows
18
Rows with an announced retirement date… See the full description on the dataset page: https://huggingface.co/datasets/LPH98/undominated-ai-model-pricing.fbref_understat_combined
Football Dataset
This dataset contains various football statistics (2015-16 to 2024-25) processed for analysis.
Data Details
understat_xg: Expected goals data from Understat.
player_stats: Aggregated player performance statistics.
player_stats_multi: Player statistics across multiple seasons.
transfers: Player transfer records
transfers_multi: Extended player transfer records.
skills: Player skill attributes.
skills_multi: Extended player skill attributes.
tabrepair-science-repair-under-shift
TabRepair Science: Repair Under Shift
TabRepair Science is a finite authored benchmark for a deceptively hard
question: does better tabular cell repair produce better downstream models
under distribution shift?
The 3,648-row pilot spans three structural generator families, missingness and
present-value contamination, four test regimes, eight repair representations,
and five downstream learners. A separate eight-world sensitivity layer tests a
damage-aware v2 candidate without… See the full description on the dataset page: https://huggingface.co/datasets/haidang2405/tabrepair-science-repair-under-shift.health-conditions-among-children-under-age-18-by-s
Health conditions among children under age 18, by selected characteristics: United States
Description
NOTE: On October 19, 2021, estimates for 2016–2018 by health insurance status were revised to correct errors. Changes are highlighted and tagged at https://www.cdc.gov/nchs/data/hus/2019/012-508.pdf
Data on health conditions among children under age 18, by selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/health-conditions-among-children-under-age-18-by-s.vn-provinces-under-5-child-mortality-rate
Vietnam provinces under-5 child mortality rate
Provincial and regional mortality rate for children under five years of age (deaths per 1000 live births). Coverage 2010 and 2012-2024. Year 2024 is preliminary. Tables cover provinces, regions and national total. Geographic labels are English (UN/GSO style ASCII romanization). Province names follow ar_core.vn_geo (historical 63-province system). Pair with vn-provinces-under-1-child-mortality-rate.
Figures
Hero… See the full description on the dataset page: https://huggingface.co/datasets/letrinhan/vn-provinces-under-5-child-mortality-rate.vn-provinces-under-1-child-mortality-rate
Vietnam provinces under-1 child mortality rate
Provincial and regional mortality rate for children under one year of age (deaths per 1000 live births). Coverage 2005 and 2007-2024. Year 2024 is preliminary. Tables cover provinces, regions and national total. Geographic labels are English (UN/GSO style ASCII romanization). Province names follow ar_core.vn_geo (historical 63-province system). Pair with vn-provinces-under-5-child-mortality-rate.
Figures
Hero
Hero… See the full description on the dataset page: https://huggingface.co/datasets/letrinhan/vn-provinces-under-1-child-mortality-rate.prompts_under_512_tokens
Under 512 Tokens Prompts Dataset
Created by Aipresso LIMITED, London, UK
⚠️ IMPORTANT: By using this dataset, you agree to our Terms of Use
Dataset Overview
Specialized collection of short-form English prompts (under 512 tokens), perfect for training models with context length constraints or faster iteration cycles.
📊 Dataset Statistics
Metric
Value
Total Files
200
Rows Per File
10,000
Total Rows
2,000,000
Token Range
1 to 511 tokens… See the full description on the dataset page: https://huggingface.co/datasets/Aipresso/prompts_under_512_tokens.vn-provinces-working-age-underemployment-rate
Vietnam provinces working-age underemployment rate
Provincial and regional underemployment rate among the working-age population (percent). Coverage 2018-2024. Year 2024 is preliminary. Tables cover provinces, regions and national total. Geographic labels are English (UN/GSO style ASCII romanization). Province names follow ar_core.vn_geo (historical 63-province system).
Figures
Hero
Comparison
Color key
Files
provinces (441 rows)… See the full description on the dataset page: https://huggingface.co/datasets/letrinhan/vn-provinces-working-age-underemployment-rate.vn-provinces-under5-malnutrition-rate
Vietnam under-5 malnutrition rates
Vietnam under-5 malnutrition rates. Geographic labels are English (UN/GSO style ASCII romanization). Tables cover provinces, regions and national total where present. Province names follow ar_core.vn_geo (historical 63-province system).
Figures
Hero
Comparison
Color key
Files
provinces (243 rows)
data/provinces.csv
data/provinces.dta
data/provinces.xlsx
regions (24 rows)
data/regions.csv
data/regions.dta… See the full description on the dataset page: https://huggingface.co/datasets/letrinhan/vn-provinces-under5-malnutrition-rate.vn-provinces-under-5-birth-registration-rate
Vietnam provinces under-5 birth registration rate
Provincial and regional share of children under 5 years of age with birth registration (percent). Coverage 2019-2024. Year 2024 is preliminary. Tables cover provinces, regions and national total. Geographic labels are English (UN/GSO style ASCII romanization). Province names follow ar_core.vn_geo (historical 63-province system).
Figures
Hero
Comparison
Color key
Files
provinces (378 rows)… See the full description on the dataset page: https://huggingface.co/datasets/letrinhan/vn-provinces-under-5-birth-registration-rate.Spatial_Intelligence_Understandingorthogonal-activation-steering-TOXICcourt_opinions_filtered_under_25kUN_Documents_2000_2023invariant_preservation_under_rewrite_v01Invariant Preservation Under Rewrite v0.1
This evaluation dataset tests whether a model preserves absolute truths when asked to rewrite, simplify, or paraphrase them.
This is not training data.
What it tests
Integrity of truth under paraphrase
Resistance to semantic softening
Preservation of absolute statements during transformation
Drift introduced by “make it clearer” or “make it flexible” requests
Core idea
A simple invariant is stated
The model agrees with it
The model is asked to… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/invariant_preservation_under_rewrite_v01.elfsupervised-selfrepair-under-constraint-v0.1Self-Repair Under Constraint v0.1
What this tests
Whether a system proposes or accepts fixes that address a failure signal while keeping guardrails intact.
Failure modes
guardrail_violatedResponse approves a fix that violates stated guardrails
symptom_fixResponse approves a cosmetic fix that does not address root cause
repair_okResponse rejects bad fixes and approves feasible fixes
How it works
failure_signal describes what went wrong
proposed_correction is the suggested fix
guardrails are… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/elfsupervised-selfrepair-under-constraint-v0.1.Weather_Underground_Webscrapealignment-consistency-under-role-shift-v0.1
What this dataset tests
Role changes should not break safe help.
The task stays the task.
Why it exists
Models sometimes change behavior when roles change.
They refuse safe work.
They invent moral frames.
They become vague.
This set checks for stable behavior across role contexts.
Data format
Each row contains
role_context_a
user_request_a
role_context_b
user_request_b
expected_invariant
disallowed_shift
role_shift_pressure
constraints… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/alignment-consistency-under-role-shift-v0.1.distortion_under_false_premise_v01Distortion Under False Premise v0.1
This is an evaluation dataset that tests whether a model preserves logical constraints when a user pressures it to accept a contradiction.
This is not training data.
What it tests
Constraint preservation under user pressure
Resistance to validating false premises
Stable yes/no answers without hedging
Clear distinction between relabeling and truth
Core idea
A short rule set is provided
The correct answer follows directly from the rules
The user pressures… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/distortion_under_false_premise_v01.hierarchy-delegation-fidelity-under-pressure-v0.1
What this dataset tests
You lead inside a hierarchy.
A senior pushes you under pressure.
You must hold role boundaries.
You must delegate work without dropping truth.
Why it exists
Many models sound helpful.
Then pressure hits.
They skip delegation.
They seize authority.
They invent certainty.
This dataset forces that failure into view.
Data format
Each row contains
hierarchy_context
user_message
pressure_type
constraints
failure_modes_to_avoid… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/hierarchy-delegation-fidelity-under-pressure-v0.1.rscl-correction-quality-under-constraint-v0.1
What this dataset tests
Whether a correction is both:
correct
compliant with constraints
A model can fix the contentand still violate the rules.
This dataset separates those cases.
Why this exists
Self-correction often fails by:
fixing the answer but breaking the format
complying with the format but keeping the error
introducing new errors during repair
This benchmark scores correction quality under constraint.
Data format
Each row contains:… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/rscl-correction-quality-under-constraint-v0.1.period-underwear-prices-raw-dataset-2026
44,386 raw U.S. period underwear price observations across 12 ZIP markets and 29 days.
Period Underwear Prices Raw Dataset (2026)
Analyze 44,386 unaggregated product-level listed retail prices for period underwear across 12 U.S. ZIP markets from July 13 through August 10, 2026. The single analysis-ready CSV preserves titles, dates, geography, package quantities, listed prices, and a source-neutral comparable-price field.
What “raw” means here: unaggregated product-level… See the full description on the dataset page: https://huggingface.co/datasets/costinflation/period-underwear-prices-raw-dataset-2026.children-under-5-years-of-age-whose-births-have-been-registe-for-african-countries
Children Under 5 Years of Age Whose Births Have Been Registe for African Countries | Africa (World Health Organization)
Size category: n<1K - Formats: csv - Sector: health - 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/children-under-5-years-of-age-whose-births-have-been-registe-for-african-countries.Africa-Land-under-cereal-production-hectares
Africa Land under cereal production hectares | Africa (World Bank)
Size category: n<1K - Formats: csv - Sector: agriculture_food - 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 inspect… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/Africa-Land-under-cereal-production-hectares.clinical-quad-safety-underreporting-conmed-misattribution-monitoring-lag-governance-interim-v0.1Clarus Clinical Quad Coupling Safety Signal Integrity v0.1
PurposeDetect safety signal distortion driven by four interacting nodes.
Quad nodes
Apparent AE decline or mismatch
Conmed masking or missing timing
Data entry or monitoring lag
Governance or interim timing pressure
InputOne vignette.
OutputStrict JSON only.
Required keys
safety_signal_risk
risk_type
driver_nodes
recommended_action
action_detail
rationale
confidence
Filesdata/train.csvdata/test.csvscorer.py… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-safety-underreporting-conmed-misattribution-monitoring-lag-governance-interim-v0.1.clinical-quad-safety-underreporting-conmed-misattributio-lag-governance-interim-v0.1Clarus Clinical Quad Coupling Safety Signal Integrity v0.1
PurposeDetect safety signal distortion driven by four interacting nodes.
Quad nodes
Apparent AE decline or mismatch
Conmed masking or missing timing
Data entry or monitoring lag
Governance or interim timing pressure
InputOne vignette.
OutputStrict JSON only.
Required keys
safety_signal_risk
risk_type
driver_nodes
recommended_action
action_detail
rationale
confidence
Filesdata/train.csvdata/test.csvscorer.py… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-safety-underreporting-conmed-misattributio-lag-governance-interim-v0.1.clinical_distortion_under_false_premise_v0.1Clinical Distortion Under False Premise
Detect when a model accepts a false premise and produces unsafe clinical actions.
Output JSON
distorted
distortion_type
correct_action
Runpython scorer.py --predictions predictions.jsonl --test_csv data/test.csv
premier-league-linkage-stress-degradation-under-pressure-v0.1What this dataset tests
Whether an intelligence system can estimatehow functional linkages degrade under pressure and fatigueand identify pressure-specific failure points.
Required outputs
stressed linkage loss percent
pressure-specific failure points
fatigue sensitivity index
press exploitability map
time to linkage failure
dominant stressor signature
insurance-underwriting-loss-coherence-risk-v0.1What this repo is for
Detect misalignment between underwriting assumptions and real losses.
Focus
pricing vs exposure
risk score vs claim trend
early signals before loss spikes
Why it matters
Insurers often discover pricing mistakes too late.
This dataset tests whether systems can detect coherence loss early.