datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
montreal_firefirmsfire-financial-ner-extractionThis dataset can be used for benchmarking LLM Structured Outputs via the code here:
https://github.com/cleanlab/structured-output-benchmark/
us_ssa_gender_neutral_first_namesThis is the official dataset for Beyond Binary Gender Labels: Revealing Gender Bias in LLMs through Gender-Neutral Name Predictions
Name-based gender prediction has traditionally categorized individuals as either female or male based on their names, using a binary classification system. That binary approach can be problematic in the cases of gender-neutral names that do not align with any one gender, among other reasons. Relying solely on binary gender categories without recognizing… See the full description on the dataset page: https://huggingface.co/datasets/uzw/us_ssa_gender_neutral_first_names.idt5-v4-results-final-lora-s123-20260912T013040606815Z
final-lora-s123-20260912T013040606815Z
Run artifacts and per-item predictions.
Phase: final. These are newly generated results, not a reproduction of the legacy TCI tables.
See run_manifest.json, rules.json, generation_protocol.json and checkpoint_hashes.json. Structural scores do not establish semantic or Bloom validity.
Metrics
{
"n": 267,
"rule_version": "structural-proxy-v0.4-grounding-separated",
"parse_success_pct": 94.7565543071161,
"bleu":… See the full description on the dataset page: https://huggingface.co/datasets/Firmansyah-Ibrahim/idt5-v4-results-final-lora-s123-20260912T013040606815Z.plants-evidence
FireApproved.com plant flammability evidence directory
Structured plant-flammability evidence from
FireApproved.com, a citation directory for
wildfire-resistant construction and plants. The site issues no ratings
of its own. Every status is computed from cited evidence.
3,801 plant records / 27,007 evidence rows, plus the 130-source
registry those rows are attributed to.
Each row keeps the source's own wording, the edition, and the date
the document was read. Classifications… See the full description on the dataset page: https://huggingface.co/datasets/fireapproved/plants-evidence.afrofinchain-multilingual-web3
AfroFinChain — Multilingual Web3 & Blockchain Dataset
Multilingual Web3 & blockchain dataset in Yoruba, Hausa, Igbo, and Nigerian Pidgin with 1,451 terminology entries and 1,451 conversational Q&A pairs. Designed for LLM fine-tuning, financial literacy, and conversational AI in low-resource African languages. Uses culturally grounded analogies (e.g., ajo, adashi, isusu) to make DeFi concepts actually understandable.
Built with Adaptive Data by Adaption as part of the Adaption… See the full description on the dataset page: https://huggingface.co/datasets/FirstBML1/afrofinchain-multilingual-web3.FiReCS
Dataset Card for Filipino-English Reviews with Code-Switching (FiReCS)
Dataset Summary
We introduce FiReCS, the first sentiment-annotated corpus of product and service reviews involving Filipino-English code-switching. The data set is composed of 10,487 reviews with a fairly balanced number per sentiment class. Inter-annotator agreement is high with a Kripendorffs’s α for ordinal metric of 0.83. Three human annotators were tasked to manually label reviews according to… See the full description on the dataset page: https://huggingface.co/datasets/ccosme/FiReCS.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.vn-provinces-mean-age-first-marriage
Vietnam provinces mean age at first marriage
Provincial and regional mean age at first marriage (years). Coverage 2010 and 2013-2024. 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 (819 rows)
data/provinces.csv
data/provinces.dta… See the full description on the dataset page: https://huggingface.co/datasets/letrinhan/vn-provinces-mean-age-first-marriage.idt5-v4-results-final-lora-s2026-20260912T034640190015Z
final-lora-s2026-20260912T034640190015Z
Run artifacts and per-item predictions.
Phase: final. These are newly generated results, not a reproduction of the legacy TCI tables.
See run_manifest.json, rules.json, generation_protocol.json and checkpoint_hashes.json. Structural scores do not establish semantic or Bloom validity.
Metrics
{
"n": 267,
"rule_version": "structural-proxy-v0.4-grounding-separated",
"parse_success_pct": 95.88014981273409,
"bleu":… See the full description on the dataset page: https://huggingface.co/datasets/Firmansyah-Ibrahim/idt5-v4-results-final-lora-s2026-20260912T034640190015Z.indo-bloom-corpus
🇮🇩 Indo-Bloom-AQG: A Unified Framework for Controllable Indonesian AQG
⚠️ RESEARCH ARTIFACT STATUS: SILVER VERSION (Work in Progress)
This dataset serves as the preliminary corpus (Silver Standard) for the ongoing Doctoral Dissertation at Universitas Negeri Malang (UM).
Current State: Unannotated / Pre-validation with Heuristic Bloom Labels
Target Final State: Gold Standard (Expert Validated with Bloom's Taxonomy Labels)
🔒 FROZEN — v0.1 Silver
This version is permanently… See the full description on the dataset page: https://huggingface.co/datasets/Firmansyah-Ibrahim/indo-bloom-corpus.vn-provinces-criminal-cases-first-instance
Vietnam criminal cases first-instance trial
Vietnam criminal cases first-instance trial. 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 (189 rows)
data/provinces.csv
data/provinces.dta
data/provinces.xlsx
regions (18 rows)
data/regions.csv… See the full description on the dataset page: https://huggingface.co/datasets/letrinhan/vn-provinces-criminal-cases-first-instance.scrape-content-dataset-v1
Scrape Content Dataset v1
A human-curated benchmark dataset for evaluating web scraping engines on content quality.
Overview
This dataset contains 1,000 web pages with human-annotated ground truth for evaluating how well web scraping engines capture core content while avoiding noise (navigation, ads, footers, etc.). The dataset was created in 2025-10-21 and may become outdated over time.
Dataset Structure
CSV format with columns:
id: Sequential identifier
url:… See the full description on the dataset page: https://huggingface.co/datasets/firecrawl/scrape-content-dataset-v1.vn-provinces-fires-explosions
Vietnam fires and explosions
Vietnam fires and explosions. 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 (189 rows)
data/provinces.csv
data/provinces.dta
data/provinces.xlsx
regions (18 rows)
data/regions.csv
data/regions.dta… See the full description on the dataset page: https://huggingface.co/datasets/letrinhan/vn-provinces-fires-explosions.idt5-v4-results-final-fft-s2026-20260911T063507183162Z
final-fft-s2026-20260911T063507183162Z
Run artifacts and per-item predictions.
Phase: final. These are newly generated results, not a reproduction of the legacy TCI tables.
See run_manifest.json, rules.json, generation_protocol.json and checkpoint_hashes.json. Structural scores do not establish semantic or Bloom validity.
Metrics
{
"n": 267,
"rule_version": "structural-proxy-v0.4-grounding-separated",
"parse_success_pct": 88.01498127340824,
"bleu":… See the full description on the dataset page: https://huggingface.co/datasets/Firmansyah-Ibrahim/idt5-v4-results-final-fft-s2026-20260911T063507183162Z.idt5-v4-results-final-lora-s42-20260912T063343815032Z
final-lora-s42-20260912T063343815032Z
Run artifacts and per-item predictions.
Phase: final. These are newly generated results, not a reproduction of the legacy TCI tables.
See run_manifest.json, rules.json, generation_protocol.json and checkpoint_hashes.json. Structural scores do not establish semantic or Bloom validity.
Metrics
{
"n": 267,
"rule_version": "structural-proxy-v0.4-grounding-separated",
"parse_success_pct": 92.88389513108615,
"bleu":… See the full description on the dataset page: https://huggingface.co/datasets/Firmansyah-Ibrahim/idt5-v4-results-final-lora-s42-20260912T063343815032Z.osfm-bml-censuses
FireApproved.com CAL FIRE OSFM Building Materials Listing — WUI category censuses
Complete public censuses of the CAL FIRE Office of the State Fire
Marshal Building Materials Listing, published by
FireApproved.com. One census per in-scope
category code, from a frozen snapshot. Every listing in a covered
category is present — a census, not a selection.
276 listings across 16 category codes (decking, siding, doors,
windows, vents, eaves, roofing, ignition-resistant and… See the full description on the dataset page: https://huggingface.co/datasets/fireapproved/osfm-bml-censuses.french_first_names_insee_2024
French First Names from Death Records (1970-2024)
This dataset contains French first names extracted from death records provided by INSEE (French National Institute of Statistics and Economic Studies) covering the period from 1970 to September 2024.
Dataset Description
Data Source
The data is sourced from INSEE's death records database. It includes first names of deceased individuals in France, providing valuable insights into naming patterns across different… See the full description on the dataset page: https://huggingface.co/datasets/eltorio/french_first_names_insee_2024.qwen35-9b-plan-first-coop
What this is
Cooperative two-agent coding dataset: 211 task pairs across 18 repos, generated with
mini_swe_agent on Qwen/Qwen3.5-9B in coop setting using a plan-first prompt variant —
agents are prompted to produce an explicit implementation plan before writing code, then coordinate
to reconcile plans before proceeding. Patches are auto-merged after both submit.
At a glance
Field
Value
Model
Qwen/Qwen3.5-9B
Agent
mini_swe_agent (plan-first prompt)… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen35-9b-plan-first-coop.idt5-v4-results-final-fft-s42-20260910T135823740810Z
final-fft-s42-20260910T135823740810Z
Run artifacts and per-item predictions.
Phase: final. These are newly generated results, not a reproduction of the legacy TCI tables.
See run_manifest.json, rules.json, generation_protocol.json and checkpoint_hashes.json. Structural scores do not establish semantic or Bloom validity.
Metrics
{
"n": 267,
"rule_version": "structural-proxy-v0.4-grounding-separated",
"parse_success_pct": 93.63295880149813,
"bleu":… See the full description on the dataset page: https://huggingface.co/datasets/Firmansyah-Ibrahim/idt5-v4-results-final-fft-s42-20260910T135823740810Z.idt5-v4-results-final-fft-s123-20260910T215641650583Z
final-fft-s123-20260910T215641650583Z
Run artifacts and per-item predictions.
Phase: final. These are newly generated results, not a reproduction of the legacy TCI tables.
See run_manifest.json, rules.json, generation_protocol.json and checkpoint_hashes.json. Structural scores do not establish semantic or Bloom validity.
Metrics
{
"n": 267,
"rule_version": "structural-proxy-v0.4-grounding-separated",
"parse_success_pct": 93.25842696629213,
"bleu":… See the full description on the dataset page: https://huggingface.co/datasets/Firmansyah-Ibrahim/idt5-v4-results-final-fft-s123-20260910T215641650583Z.snt-fire-enose-sample
SNT Fire/Smoke E-Nose - Sample Data Subset
A small, curated sample of raw recordings from SmartNanotubes' 4×16-channel carbon-nanotube (CNT) electronic-nose arrays, released so that researchers and partners can see the signal quality and experiment with the data. This is a teaser subset, not the full training corpus.
It accompanies the model card at smartnanotubes/snt-fire-enose-5class and the interactive demo at smartnanotubes/snt-fire-enose-demo.
What's in it… See the full description on the dataset page: https://huggingface.co/datasets/smartnanotubes/snt-fire-enose-sample.canada_ssa_gender_neutral_first_namesThis is the official dataset for Beyond Binary Gender Labels: Revealing Gender Bias in LLMs through Gender-Neutral Name Predictions
Name-based gender prediction has traditionally categorized individuals as either female or male based on their names, using a binary classification system. That binary approach can be problematic in the cases of gender-neutral names that do not align with any one gender, among other reasons. Relying solely on binary gender categories without recognizing… See the full description on the dataset page: https://huggingface.co/datasets/uzw/canada_ssa_gender_neutral_first_names.article_2019_first_500first_dataset_iabdExtraído de https://github.com/anthony-wang/BestPractices/tree/master/data.
Campos:
Formula (string)
T (float64): Temperatura (K)
CP (float64): Capacidad calorífica (J/mol K)
firm-shoe-3dd73b
firm-shoe-3dd73b
Synthetic weather test data: 40 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/mark-miller/firm-shoe-3dd73b.ice_and_fire
Ice and Fire Comment Dataset
Description
The Ice and Fire Dataset is a collection of comments from the Icelandic blog platform, blog.is, that have been annotated in several tasks.
Dataset Structure
Data Fields
annotator_id: An integer identifier for the annotator who labeled the comment.
label: The label assigned to the comment.
task_type: The type of task the comment was annotated for (see paper).
show_blog_post: A boolean indicating whether the… See the full description on the dataset page: https://huggingface.co/datasets/hafsteinn/ice_and_fire.qwen35-9b-question-first-coop-random-50
What this is
Cooperative two-agent coding dataset: 49 task pairs across 15 repos (random-50 subset), generated
with mini_swe_agent on Qwen/Qwen3.5-9B in coop setting using a question-first prompt variant —
agents begin by asking each other clarifying questions about their respective features before
starting implementation, aiming to surface integration concerns early. All 49 pairs were
successfully evaluated.
At a glance
Field
Value
Model… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen35-9b-question-first-coop-random-50.prop-firm-industry-analysis-2026
Proprietary Trading Firm Industry Dataset (2026)
Dataset Description
This dataset provides a structured, multi-table overview of the proprietary (prop) trading firm industry as of early 2026. It covers 31 firms across four complementary CSV files, capturing firm characteristics, evaluation program structures, payout policies, and aggregate industry-level metrics.
The dataset is intended for researchers, analysts, and practitioners studying the retail-facing… See the full description on the dataset page: https://huggingface.co/datasets/fsvf/prop-firm-industry-analysis-2026.