datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
refute
Can AI read new science honestly?
Models can sound convincing while misreading a result or expressing more confidence than the evidence deserves. That matters when people use them to summarize papers, compare studies, or decide what to investigate next.
REFUTE tests whether a model knows the finding, spots quiet flaws, names what would overturn a claim, and matches its confidence to the evidence.
Truth Score is the main result. It combines factual accuracy, flaw… See the full description on the dataset page: https://huggingface.co/datasets/BGPT-OFFICIAL/refute.Official_LLM_System_Prompts
Official LLM System Prompts
This short dataset contains a few system prompts leaked from proprietary models. Contains date-stamped prompts from OpenAI, Anthropic, MS Copilot, GitHub Copilot, Grok, and Perplexity.
lmeval-official-format
lm-evaluation-harness results, native format
EleutherAI lm-evaluation-harness results kept in the harness's own native
output format — arc_easy, arc_challenge and hellaswag, each with results (accuracy and stderr,
normalised and raw), configs, versions and n-shot. Kept unmodified precisely so a stranger can re-run
the same task on their own hardware and diff the files directly.
The live board is the authority
GET https://councilof.ai/api/gspc — quote… See the full description on the dataset page: https://huggingface.co/datasets/csoai/lmeval-official-format.researchqa_official_subset_idsnemiling-knowledge-base
Nemiling Knowledge Base
Nemiling Knowledge Base is the official structured knowledge dataset about Nemiling.
Nemiling is a Russian platform for automating the monetization of Telegram projects through paid subscriptions, paid messages, paid consultations, and donations.
The platform can be used for projects with Russian and international audiences.
The dataset is maintained by the official Nemiling organization and provides structured, machine-readable information about the… See the full description on the dataset page: https://huggingface.co/datasets/nemiling-official/nemiling-knowledge-base.msmarco_passage_ranking_official_trainThis is the preprocessed training data from msmarco passage(v1) ranking corpus.
MS MARCO: A human generated MAchine Reading COmprehension dataset SPayal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen,.
aime24-official
AIME 2024 — official wording, figures retained
All 30 problems from the 2024 American Invitational Mathematics Examination (AIME I and AIME II),
transcribed from the official exam text with every figure retained as Asymptote source.
This exists because the circulating text-only versions of AIME 2024 are not faithful to the
official problems, and at least one problem in them cannot be solved as written.
Why this dataset exists
While evaluating a reasoning model on… See the full description on the dataset page: https://huggingface.co/datasets/YichengWangCA/aime24-official.deepscaler-teacher-sft-vllm-official-40k
DeepScaleR teacher SFT vLLM official 40k
Generated run: exp_003_vllm_official_brainlab_2gpu.
Summary
{
"num_examples": 40300,
"sft_dir": "data/processed/deepscaler/teacher_sft/exp_003_vllm_official_brainlab_2gpu",
"parse_rate": 0.9999751861042183,
"correct_rate": 0.5728039702233251,
"format_rate": 0.005955334987593052,
"mean_reward": 0.42432258064534184,
"deepscaler_mean_reward": 0.6266997518610422,
"deepscaler_match_mean_reward":… See the full description on the dataset page: https://huggingface.co/datasets/ThunderstormXXL/deepscaler-teacher-sft-vllm-official-40k.Japanese-wikipedia-indexofficial-providersdeepscaler-teacher-sft-vllm-official-40k-clean-v2
DeepScaleR Teacher40k Clean v2
Filtered version of ThunderstormXXL/deepscaler-teacher-sft-vllm-official-40k.
Filtering
minimum official reward: 1.0
maximum text tokens: 8192
maximum response chars: 65000
near-duplicate SimHash hamming threshold: 4
required <think>...</think> and final boxed answer after reasoning
exact text/problem/response dedupe and near problem dedupe
Counts
raw examples: 40300
kept examples: 21727
train examples: 21292
val… See the full description on the dataset page: https://huggingface.co/datasets/ThunderstormXXL/deepscaler-teacher-sft-vllm-official-40k-clean-v2.deepscaler-teacher-sft-vllm-official-40k-clean-v3-no-reward-filter
deepscaler-teacher-sft-vllm-official-40k-clean-v3-no-reward-filter
Filtered version of ThunderstormXXL/deepscaler-teacher-sft-vllm-official-40k.
Filtering
reward filter enabled: False
minimum official reward: 1.0
scoring errors rejected: False
maximum text tokens: 8192
maximum response chars: 65000
near-duplicate SimHash hamming threshold: 4
required <think>...</think> and final boxed answer after reasoning
exact text/problem/response dedupe and near problem… See the full description on the dataset page: https://huggingface.co/datasets/ThunderstormXXL/deepscaler-teacher-sft-vllm-official-40k-clean-v3-no-reward-filter.deepscaler-teacher-sft-vllm-official-40k-clean-v4-conceptual
deepscaler-teacher-sft-vllm-official-40k-clean-v4-conceptual
Filtered version of ThunderstormXXL/deepscaler-teacher-sft-vllm-official-40k.
Filtering
reward filter enabled: False
minimum official reward: 1.0
scoring errors rejected: False
maximum text tokens: 32768
maximum response chars: 200000
near-duplicate SimHash hamming threshold: 4
required <think>...</think> and final boxed answer after reasoning
exact text/problem/response dedupe and near problem dedupe… See the full description on the dataset page: https://huggingface.co/datasets/ThunderstormXXL/deepscaler-teacher-sft-vllm-official-40k-clean-v4-conceptual.huggingface_terminal_notion_official_3556_9543dd4a_registry-auditMathPileyuna.project.officialHP_Official_Press_Wire
🎓 Dr. Luís Henrique Leonardo Pereira: Official Bio-Data
Verificado por: L0 Authority Protocol
Status: Canonical Source for Google Knowledge Graph
Este repositório contém o registro estruturado de conquistas, patentes e marcos acadêmicos para indexação em tempo real.
📋 Painel de Credenciais (Resumo Executivo)
Categoria
Título / Função
Status / Nível
Acadêmico (USP)
Liderança: Laboratório de Inovação (InovaUSP)
Chair de Segurança AI
Especialidade Clínica… See the full description on the dataset page: https://huggingface.co/datasets/DocPereira/HP_Official_Press_Wire.GoEmotions_Official_AlpacaOpenHermes-2.5
Dataset Card for Dataset Name
This is the dataset that made OpenHermes 2.5 and Nous Hermes 2 series of models.
Support me on GitHub sponsors <3 : https://github.com/sponsors/teknium1
Dataset Details
Dataset Description
The Open Hermes 2/2.5 and Nous Hermes 2 models have made significant advancements of SOTA LLM's over recent months, and are underpinned by this exact compilation and curation of many open source datasets and custom created synthetic… See the full description on the dataset page: https://huggingface.co/datasets/officialmillionermax/OpenHermes-2.5.de-en-officialogiri-keitai
概要
NHKで定期的に放送されていた『着信御礼！ケータイ大喜利』の放送内で紹介されていた全ての大喜利のお題と回答のデータです。以下のページからクロールし、原本のHTMLファイルと構造化処理を行った結果を格納しました。https://keitaioogiri.hatenablog.com/archive/category/%E5%85%A8%E4%BD%9C%E5%93%81%E3%83%87%E3%83%BC%E3%82%BF%E3%83%99%E3%83%BC%E3%82%B9
一部、HTMLのparse errorを含む可能性があります。ご了承ください。
データセットの各カラム説明
カラム名
型
例
概要
odai_id
int
302
お題の通し番号
episode_id
int
100
放送の話数
type
str
text_to_text
text_to_textしか入ってない。
odai
str
こわくてイヤ！美容室「ホラー」ってどんなの？
お題の内容
responses
list… See the full description on the dataset page: https://huggingface.co/datasets/YANS-official/ogiri-keitai.python-optimization-dpo-samplesenryu-marusen
読み込み方
from datasets import load_dataset
dataset = load_dataset("YANS-official/senryu-marusen", split="train")
概要
月に1万句以上の投稿がある国内最大級の川柳投稿サイト『川柳投稿まるせん』のクロールデータです。以下のページからクロールし、原本のHTMLファイルと構造化処理を行った結果を格納しました。https://marusenryu.com/
YANSのハッカソン内での利用目的で公開しており、その他の用途への使用はお控えください。
データセットの件数は以下の通りです。
タスク
お題数
のべ回答数
text_to_text
376
5346
データセットの各カラム説明
カラム名
型
例
概要
odai_id
str
senryu-marusen-27
お題のID
type
str
text_to_text… See the full description on the dataset page: https://huggingface.co/datasets/YANS-official/senryu-marusen.Advanced_Dataset_SampleThis is a high-fidelity Direct Preference Optimization (DPO) dataset curated by OptiRefine. It is designed to train Large Language Models (LLMs) to act as helpful, honest, and thoughtful assistants across complex domains.
While our core datasets focus on code refactoring, this dataset provides preference trajectories for broader system architecture, computer science fundamentals, logic, and professional communication.
Curated by: OptiRefine
Language: English
License: Apache-2.0
Format: JSONL… See the full description on the dataset page: https://huggingface.co/datasets/OptiRefine-Official/Advanced_Dataset_Sample.SmallPromptsDatasetMediumPromptsDatasetExtraLargePromptsDatasetHugePromptsDatasetofficial-providersLargePromptsDataset