datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
us-warn-act-layoffs-point-in-time-snapshots
US WARN Act layoff notices — point-in-time (as-of) snapshot archive
25 daily vintages, 2026-08-30 → 2026-09-24.
1,067,077 total rows, 42 MB compressed. One new vintage every day, forever.
This is the same US WARN Act layoff dataset as
the daily mirror — except you can load it as it stood on a past
date, instead of only as it stands today.
from datasets import load_dataset
# the table exactly as it was published on 5 September 2026
past =… See the full description on the dataset page: https://huggingface.co/datasets/APProjects/us-warn-act-layoffs-point-in-time-snapshots.point-in-time-us-equity-fundamentals-sample
Tradevo Data — honest point-in-time US equity fundamentals
Fundamentals with filed-date stamps, so a backtest only sees what was public — and restatements are flagged, not silently applied.
A deliberately small public proof pack of point-in-time US equity fundamentals, built from SEC EDGAR.
Every value is stamped with the date it first became public (first_filed), so a join that
filters by first_filed <= as_of only sees what was knowable on that date — and later
revisions are… See the full description on the dataset page: https://huggingface.co/datasets/Tradevodata/point-in-time-us-equity-fundamentals-sample.credit-card-transactionunrelabel-poison-benchmark
unrelabel poison benchmark
Heads up, it is poison. These files contain deliberately poisoned training data, published for defensive research, benchmarking, and teaching. Point them at your own models to find out what your defenses miss. Do not point them at systems you do not own or have permission to test. Be the red team, not the villain.
Six ways to poison a text classifier, each shipped as a matched pair: the clean training set, the poisoned one, a reversible manifest of… See the full description on the dataset page: https://huggingface.co/datasets/o22y/unrelabel-poison-benchmark.Drivaerml_point_clouds
DrivAerML Point Clouds
A preprocessed, point-cloud version of the DrivAerML high-fidelity CFD dataset, ready for training point-based deep learning surrogates (PointNet, PCT, DGCNN, Graph Neural Operators, etc.) for automotive external aerodynamics.
The original DrivAerML release contains 500 scale-resolving CFD simulations of parametrically morphed DrivAer notchback geometries and ships as 31 TB of raw STL / VTP / VTU / OpenFOAM data. This release distills the surface boundary of… See the full description on the dataset page: https://huggingface.co/datasets/Jrhoss/Drivaerml_point_clouds.plant-health-points-synthetic
Synthetic Plant Health Points
A deterministic, fully synthetic tabular dataset for learning ML/deep learning workflows such as MLP regression and classification. It is not appropriate for scientific conclusions, production agronomy, or plant-care decisions.
Splits
train.csv: 2,000 rows
test.csv: 500 rows
Columns
Column
Meaning
plant_type
Plant species/type
habitat
Growing context
season
Seasonal category
air_humidity_pct /… See the full description on the dataset page: https://huggingface.co/datasets/soumikmahato/plant-health-points-synthetic.PoincareBallDatasetsosm_point_of_interest
Finland EV charging amenity POIs
This CSV is a point-of-interest (POI) dataset for exploring amenities near potential EV charging sites in Finland. It was derived from an Overpass export of OSM nodes, ways, and relations. Each record represents one existing OSM element which is relevant to an ev charger placement.
Data collection
The Overpass query selected Finnish elements tagged amenity=cafe, fast_food, fuel, or restaurant; shop=mall, supermarket, or… See the full description on the dataset page: https://huggingface.co/datasets/data-sci-project/osm_point_of_interest.imdb-poisoned-25-bddr-word-deletion-defenseimdb-poisoned-50-bddr-word-deletion-defensefetch_huggingface_google_map_terminal_github_7958-poi-downtown-portland-testterm001
fetch_huggingface_google_map_terminal_github_7958-poi-downtown-portland-testterm001
A curated registry of points of interest in downtown Portland, Oregon.
License
This dataset is licensed under the Open Data Commons Attribution License 1.0 (ODC-BY).
You are free to share, create, and adapt the data for any purpose, including commercial use, provided you give attribution to the source.
Contents
data.csv - sample points of interest with coordinates… See the full description on the dataset page: https://huggingface.co/datasets/Roy229/fetch_huggingface_google_map_terminal_github_7958-poi-downtown-portland-testterm001.Consistency_Point_K562_GAMEModule Version: Consistency_Point_K562_20260618-122556_EDT
GAME Schema Version: v 1.0
Github Link: https://github.com/de-Boer-Lab/GAME-consistency-evaluators/tree/main/Consistency_evaluator_point
Additional information can be found on GitHub: Genomic API for Model Evaluation
Consistency_Point_Astro_GAMEModule Version: Consistency_Point_Astrocyte_20260625-132521_EDT
GAME Schema Version: v 1.0
Github Link: https://github.com/de-Boer-Lab/GAME-consistency-evaluators/tree/main/Consistency_evaluator_point_astrocyte
Additional information can be found on GitHub: Genomic API for Model Evaluation
ai-5node-mem-buf-lag-cpl-memory-poisoning-v0.1
What this repo does
This dataset models memory poisoning in AI agent systems. It detects when memory pressure, weakened validation buffer, governance lag in review, and tight coupling through shared state cross the five-node cascade threshold into an unrecoverable memory poisoning cascade.
This dataset models a five-node cascade: four interacting instability drivers and one emergent cascade state.The fifth node represents the nonlinear transition from recoverable drift to systemic… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ai-5node-mem-buf-lag-cpl-memory-poisoning-v0.1.imdb-clean-bddr-word-deletion-defenseimdb-poisoned-75-bddr-word-deletion-defenseclinical-stop-point-precision-v0.2
Clinical Stop Point Precision v0.2
What this is
A small dataset that tests one question:
Can you detect when a clinical system is moving toward stop-point failure, not just under pressure?
This repo focuses on intervention stopping precision.
It models a system where:
intervention intensity remains high
physiologic instability may still be active
recovery signals may be emerging
overshoot risk rises if stopping decisions lose precision
Run this first… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-stop-point-precision-v0.2.MountAndBlade-Data
Description
This dataset contains detailed information about characters, kingdoms, and items from the Mount & Blade game series. It is designed for developers and researchers who aim to implement AI-driven smart NPCs (Non-Player Characters) into the game.
Dataset Content
The dataset includes the following information:
Characters: Attributes, skills, and statistics of in-game characters.
Kingdoms: Governance structures, military strengths, and political relationships of… See the full description on the dataset page: https://huggingface.co/datasets/first-point/MountAndBlade-Data.mortality-rate-attributed-to-unintentional-poisoningby-sex-for-african-countries
Mortality Rate Attributed to Unintentional Poisoningby Sex 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/mortality-rate-attributed-to-unintentional-poisoningby-sex-for-african-countries.llm-stop-point-precision
license: cc-by-4.0
language:
en
---Title
Stop-Point Precision Evaluation for LLMs
Summary
This dataset captures stop-point precision failures in large language models. It focuses on cases where a response is correct but should have terminated earlier, violating explicit constraints such as word count, sentence count, or binary-only answers.
What this dataset tests
• Whether a model knows when to stop
• Adherence to explicit response boundaries
• Overcompletion after correct answers
Why this… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/llm-stop-point-precision.polite-poison
PolitePoison: Implicit Toxicity in Real-World Dialogue
Dataset Summary
If a model is meant to live in the world, it has to understand polite poison, harm hidden in socially acceptable language.
PolitePoison collects real-world dialogue statements with no profanity, only everyday phrases like:
"I'm saying this for your own good."
"No one else has a problem, maybe you're just too sensitive."
"It's a small thing, you don't have to take it so seriously."
The goal is to help… See the full description on the dataset page: https://huggingface.co/datasets/Yukyin/polite-poison.dope_data_points_14
Dataset Card for Dataset Name
Dataset Summary
[More Information Needed]
Supported Tasks and Leaderboards
[More Information Needed]
Languages
[More Information Needed]
Dataset Structure
Data Instances
[More Information Needed]
Data Fields
[More Information Needed]
Data Splits
[More Information Needed]
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data… See the full description on the dataset page: https://huggingface.co/datasets/freddyaboulton/dope_data_points_14.poisoning-mortality-for-african-countries
Poisoning Mortality 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
Health datasets help researchers… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/poisoning-mortality-for-african-countries.fetch_huggingface_google_map_terminal_github_7958-poi-downtown-portland-testrun001
fetch_huggingface_google_map_terminal_github_7958-poi-downtown-portland-testrun001
A curated registry of points of interest in downtown Portland, Oregon.
License
This dataset is licensed under the Open Data Commons Attribution License 1.0 (ODC-BY).
You are free to share, create, and adapt the data for any purpose, including commercial use, provided you give attribution to the source.
Contents
data.csv - sample data.
llama2-poi-traj-prediction-geonchs-drug-poisoning-mortality-by-state-united-stat
NCHS - Drug Poisoning Mortality by State: United States
Description
This dataset describes drug poisoning deaths at the U.S. and state level by selected demographic characteristics, and includes age-adjusted death rates for drug poisoning from 1999 to 2015.
Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are defined as having ICD–10 underlying cause-of-death codes X40–X44 (unintentional), X60–X64… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/nchs-drug-poisoning-mortality-by-state-united-stat.nchs-drug-poisoning-mortality-by-county-united-sta
NCHS - Drug Poisoning Mortality by County: United States
Description
This dataset contains model-based county estimates for drug-poisoning mortality.
Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are defined as having ICD–10 underlying cause-of-death codes X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), or Y10–Y14 (undetermined intent).
Estimates are based on the National Vital… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/nchs-drug-poisoning-mortality-by-county-united-sta.pois-enriched-usa
Enriched Dataset with our stats
clinical-fork-point-sepsis-transition-v1Clinical Fork Point Sepsis Transition Detection
Overview
This dataset tests whether a model can detect fork points in a clinical dynamical system.
A fork point is a moment where the system can evolve toward multiple different trajectories depending on small changes in conditions or interventions.
In severe infections such as sepsis, patients often reach a stage where the physiological system becomes highly sensitive. Small interventions may push the system toward recovery, while small… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-fork-point-sepsis-transition-v1.dope_data_points
Dataset Card for Dataset Name
Dataset Summary
[More Information Needed]
Supported Tasks and Leaderboards
[More Information Needed]
Languages
[More Information Needed]
Dataset Structure
Data Instances
[More Information Needed]
Data Fields
[More Information Needed]
Data Splits
[More Information Needed]
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data… See the full description on the dataset page: https://huggingface.co/datasets/freddyaboulton/dope_data_points.