datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ade_corpus_v2_classification
ADE-Corpus-V2 Dataset: Adverse Drug Reaction Data.
This is a dataset for classification if a sentence is ADE-related (True) or not (False).
Train size: 17,637
Test size: 5,879
Source dataset
Paper
ai-detector-data
AI Detector Predictions Dataset
A continuously-growing collection of AI text detection predictions with optional user feedback, generated from the AI Text Detector Space.
Every time someone analyzes text or a URL on the Space, the prediction is appended to this dataset. Users can also click "Correct" or "Incorrect" to provide feedback, which gets stored alongside the prediction.
Schema
Field
Type
Description
id
string
Unique 12-char hex identifier… See the full description on the dataset page: https://huggingface.co/datasets/adaptive-classifier/ai-detector-data.midi-classical-music-toio-json
MIDI Classical Music
drengskapur/midi-classical-musicのデータセットをtoioの soundコマンドで再生しやすいように以下のフォーマットのjsonに変換したデータを含めたデータセット
data format
[
{
"track_name": "ALBENIZ: Aragon Op 47/6",
"priority": 1,
"notes": [
{
"note_number": 77,
"start_time_ms": 0,
"duration_units": 26
},
{
},
},
{
"track_name": "apurdam@pcug.org.au",
"priority": 2,
"notes": [
{
"note_number": 53,
"start_time_ms": 0… See the full description on the dataset page: https://huggingface.co/datasets/ayousanz/midi-classical-music-toio-json.en-document-classification
English Document Classification Dataset
This dataset provides a curated subset of the first 1 million rows from the allenai/c4 (English configuration), enriched with multi-perspective topic annotations. It is designed for researchers exploring document classification, domain adaptation, and label noise in massive web-crawled corpora.
Dataset Summary
The dataset integrates predictions from classification models to provide a holistic view of each document’s content.… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/en-document-classification.chinese-classical-corpus
Chinese Classical Corpus
🔗 源码 & 构建脚本: github.com/gujilab/chinese-classical-corpus — 完整抽取 pipeline、14 个 Python 脚本、验证套件
🎯 配套评测基准: gujilab/chinese-classical-bench — 500 道题 × 5 任务，测 LLM 古典文献能力（题目均从本语料抽样）
中国古典文献结构化语料集，含完整十三经 + 说文解字 + 资治通鉴 + 二十四史前 15 部，以及 197 万条古译今/今译古/断句指令对。
全部 CC0 公有领域，可商用、可改用、无附加限制。
为什么做这个
中文（尤其文言文）常被说成"高密度优势"。本语料集 + 配套评测想把这个论点变成可验证的数字 —— 包括它在哪些场景成立、在哪些场景不成立。
Tokenizer 层面 —— 真成立
7 个主流 tokenizer 横评（tokenizer_study）：
DeepSeek-V3 /… See the full description on the dataset page: https://huggingface.co/datasets/gujilab/chinese-classical-corpus.kinopoisk-sentiment-classificationCOPA-SR
COPA-SR
(The dataset uses cyrillic script. For the latin version, see this dataset.)
The COPA-SR dataset (Choice of plausible alternatives in Serbian) is a translation of the English COPA dataset by following the XCOPA dataset translation methodology .
The dataset consists of 1,000 premises (My body cast a shadow over the grass), each given a question (What is the cause? / What happened as a result?), and two choices (The sun was rising; The grass was cut), with a label encoding… See the full description on the dataset page: https://huggingface.co/datasets/classla/COPA-SR.ru-scibench-grnti-classificationLLMTrace_classification
LLMTrace - Classification Dataset
🌐 LLMTrace Website |
📜 LLMTrace Paper on arXiv |
🤗 LLMTrace - Detection Dataset |
🤗 GigaCheck classification model |
This repository contains the Classification portion of the LLMTrace project. This dataset is specifically designed for the binary classification of texts as either human-written or AI-generated.
For full details on the data collection methodology, statistics, and experiments, please refer to… See the full description on the dataset page: https://huggingface.co/datasets/iitolstykh/LLMTrace_classification.multilingual-safety-classification-dataset
Multilingual Safety Classification Dataset
A multilingual dataset for safety classification across 60 languages, created by Hasan Kurşun through machine translation of English safety prompts using NLLB-200-3.3B.
Dataset Details
Processed by: Hasan KurşunAuthor: Hasan KurşunYear: 2025Source Dataset: mvrcii/safety-moderation-benchmarkTranslation Model: facebook/nllb-200-3.3B
Languages (60)
African Languages (16): Amharic, Hausa, Kinyarwanda, Luganda… See the full description on the dataset page: https://huggingface.co/datasets/hasankursun/multilingual-safety-classification-dataset.fineweb_class5-0adaption-defi-wallet-risk-classification
This dataset is a remastered version prepared using Adaption's Adaptive Data platform.
adaption-defi_wallet_risk_classification
This dataset contains prompt-completion pairs for classifying the 14-day risk outcomes of DeFi wallets on various EVM networks. Each entry provides behavioral features such as transaction counts, action ratios, and concentration metrics within a specific feature window to predict a binary risk label. The completions offer a concise justification for… See the full description on the dataset page: https://huggingface.co/datasets/samscript18/adaption-defi-wallet-risk-classification.COPA-MK
COPA-MK
The COPA-MK dataset (Choice of plausible alternatives in Macedonian) is a translation of the [English COPA dataset ]https://people.ict.usc.edu/~gordon/copa.html) by following the XCOPA dataset translation methodology.
The dataset consists of 1,000 premises (My body cast a shadow over the grass), each given a question (What is the cause? / What happened as a result?), and two choices (The sun was rising; The grass was cut), with a label encoding which of the choices is more… See the full description on the dataset page: https://huggingface.co/datasets/classla/COPA-MK.headline-classificationru-scibench-oecd-classificationru-reviews-classificationmulti-domain-document-classification
multi_domain_document_classification
Multi-domain document classification datasets.
Biomedical: chemprot, rct-sample
Computer Science: citation_intent, sciie
Customer Review: amcd, yelp_review
Social Media: tweet_eval_irony, tweet_eval_hate, tweet_eval_emotion
The yelp_review dataset is randomly downsampled to 2000/2000/8000 for test/validation/train.
chemprot
citation_intent
hyperpartisan_news
rct_sample
sciie
amcd
yelp_review
tweet_eval_irony
tweet_eval_hate… See the full description on the dataset page: https://huggingface.co/datasets/asahi417/multi-domain-document-classification.inappropriateness-classificationen-document-format-classification
English Document Format Classification Dataset
English-language web pages classified by document type, designed to train robust text classifiers and provide ready-to-use data for specific web formats.
Purpose: Train generalized document classifiers or extract clean, single-format corpora for specific downstream tasks.
Configurations: Each document type is available in its own dedicated dataset configuration (e.g., TutorialHow-ToGuide, PersonalAboutPage).
Splits: The All… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/en-document-format-classification.ParlaSent
The multilingual sentiment dataset of parliamentary debates ParlaSent 1.0
Dataset Summary
This dataset was created and used for sentiment analysis experiments.
The dataset consists of five training datasets and two test sets. The test sets have a _test.jsonl suffix and appear in the Dataset Viewer as _additional_test.
Each test set consists of 2,600 sentences, annotated by one highly trained annotator. Training datasets were internally split into "train", "dev" and "test"… See the full description on the dataset page: https://huggingface.co/datasets/classla/ParlaSent.en-document-topic-classification
English Document Topic Classification Dataset
English-language web pages classified by document topic, designed to train robust text classifiers and provide ready-to-use data for specific web topics.
Purpose: Train generalized document classifiers or extract clean, single-topic corpora for specific downstream tasks.
Configurations: Each document topic is available in its own dedicated dataset configuration (e.g., HomeGardening, GamesRecreation).
Splits: The All configuration… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/en-document-topic-classification.filter_class_1astro-classification-redshifts
AstroClassification and Redshifts Datasets
This dataset was used for the AstroClassification and Redshifts introduced in Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations. This is a dataset of simulated astronomical time-series (e.g., supernovae, active galactic nuclei), and the task is to classify the object type (AstroClassification) or predict the object's redshift (Redshifts).
Repository: https://github.com/helenqu/connect-later
Paper: will be… See the full description on the dataset page: https://huggingface.co/datasets/helenqu/astro-classification-redshifts.wos_hierarchical_multi_label_text_classificationIntroduced by du Toit and Dunaiski (2024) Introducing Three New Benchmark Datasets for Hierarchical Text Classification.
The WOS Hierarchical Text Classification are three dataset variants created from Web of Science (WOS) title and abstract data categorised into a hierarchical, multi-label class structure. The aim of the sampling and filtering methodology used was to create well-balanced class distributions (at chosen hierarchical levels). Furthermore, the WOS_JTF variant was also created… See the full description on the dataset page: https://huggingface.co/datasets/marcelsun/wos_hierarchical_multi_label_text_classification.slop-classification
Slop classifier dataset
A human-annotated dataset for studying and classifying AI-generated text that people perceive as “AI slop.”
The dataset is built from samples collected from existing public datasets and annotated through the Bench Labs SlopFinder interface.
Slop score
Each sample receives a score based on human votes:
-1 = definitely slop
0 = undecided / neutral
+1 = not slop at all
The score represents human judgment, not an objective measure of quality… See the full description on the dataset page: https://huggingface.co/datasets/bench-labs/slop-classification.philosophy-classics-structured
Classical Decision Frameworks — Philosophy Dataset
Structured public domain philosophical texts focused on decision-making, leadership,
and organizational ethics. All content is in the public domain.
Content
Works from classical philosophy structured for AI analysis:
Stoic decision principles (Marcus Aurelius, Epictetus, Seneca)
Political philosophy (Machiavelli, Aristotle)
Virtue ethics (Aristotle, Plato)
Sources
All works published before 1928… See the full description on the dataset page: https://huggingface.co/datasets/gmahia/philosophy-classics-structured.audio-event-classification-post-public
audio-event-classification-post-public
Sound-event and acoustic-scene classification annotations: ESC-50 (environmental), UrbanSound8K, FSD50k (50k+ events), TUT-Acoustic-Scenes-2017, DCASE-2025, NonSpeech7k (vocal sounds), VocalSound (laugh/cough/sigh). Useful for training audio LLMs on the perception substrate underneath higher-level reasoning.
Audio is not bundled in this repo. See download.sh and per-dataset data/<name>.info.json for the fetch recipe; run postlink_audio.py… See the full description on the dataset page: https://huggingface.co/datasets/vhands/audio-event-classification-post-public.chinese-classical-corpus
Chinese Classical Corpus
🔗 Source code & build scripts: github.com/zi6me/chinese-classical-corpus — full extraction pipeline, 14 Python scripts, validation suite.
中国古典文献结构化语料集，含完整十三经 + 说文解字 + 资治通鉴 + 二十四史前 15 部，以及 197 万条古译今/今译古/断句指令对。
全部 CC0 公有领域，可商用、可改用、无附加限制。
Quick Start
from datasets import load_dataset
# 源语料 (12,005 条章节级记录, 17.2M 字)
corpus = load_dataset("dzxr/chinese-classical-corpus", "corpus", split="train")
# 古译今 / 今译古 双向指令数据 (1,924,378 条)
translate =… See the full description on the dataset page: https://huggingface.co/datasets/flowerone/chinese-classical-corpus.arxiv-classifier
arXiv Classifier Data
Usage:
from datasets import load_dataset, DownloadMode
# download from HuggingFace
dataset = load_dataset('mlcore/arxiv-classifier', name=<CONFIG NAME>)
# load from G2
dataset = load_dataset('/share/nikola/arxiv_classifier/data/arxiv-classifier', name=<CONFIG NAME>)
To force the dataset to be re-generated:
dataset = load_dataset('/share/nikola/arxiv_classifier/data/arxiv-classifier', name=<CONFIG NAME>, download_mode=DownloadMode.FORCE_REDOWNLOAD)
See:… See the full description on the dataset page: https://huggingface.co/datasets/kilian-group/arxiv-classifier.COPA-SR_lat
COPA-SR_lat
(The dataset uses latin script. For the original (cyrillic) version, see this dataset.)
The COPA-SR dataset (Choice of plausible alternatives in Serbian) is a translation of the English COPA dataset by following the XCOPA dataset translation methodology , transliterated into Latin script.
The dataset consists of 1,000 premises (My body cast a shadow over the grass), each given a question (What is the cause? / What happened as a result?), and two choices (The sun was… See the full description on the dataset page: https://huggingface.co/datasets/classla/COPA-SR_lat.