datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
total-300-random-jh-epoch4
total-300-random-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.3890625
Action score: 0.440625
Valid samples: 320/320
rank_llm_datavsr_random
VSR: Visual Spatial Reasoning
This is the random set of VSR: Visual Spatial Reasoning (TACL 2023) [paper].
Usage
from datasets import load_dataset
data_files = {"train": "train.jsonl", "dev": "dev.jsonl", "test": "test.jsonl"}
dataset = load_dataset("cambridgeltl/vsr_random", data_files=data_files)
Note that the image files still need to be downloaded separately. See data/ for details.
Go to our github repo for more introductions.
Citation
If you find VSR… See the full description on the dataset page: https://huggingface.co/datasets/cambridgeltl/vsr_random.vertebrate-v1-issue473-fullwindow-cds-random-val
marin-dna/vertebrate-v1-issue473-fullwindow-cds-random-val
CDS full-window vertebrate projection sequences for the issue #473 random
validation control. The source is the immutable issue #417 accepted-sequence
table.
The split uniformly samples 16,384 original-orientation CDS rows
without replacement using seed 42. Sampling occurs before
reverse-complement augmentation. Selected rows are removed from training;
reverse complements are then added only to the remaining training… See the full description on the dataset page: https://huggingface.co/datasets/marin-dna/vertebrate-v1-issue473-fullwindow-cds-random-val.msmarco_passage_ranking_corpusThis is the preprocessed 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,.
synthetic-social-networks
Synthetic Social Networks (Dataset)
Raw experimental outputs from the Synthetic Social Networks study:
59,776 in-character LLM-agent posts from 528 production trials, and
64,562 posts total when the original pipeline-verification runs are
included. The artifact combines an exploratory stage with a separately
frozen, preregistered 448-trial matched-exposure confirmation. Each production
trial includes peer-vote traces from in-character voting by other agents.… See the full description on the dataset page: https://huggingface.co/datasets/ranausmans/synthetic-social-networks.tiny-random-model-summaryrandom005scaffold
SCAFFOLD
SCAFFOLD: A Large-Scale Structured Dataset of Computer Science Research Figures with Diagram QA and Chain-of-Thought Reasoning Traces is a large-scale multimodal reasoning dataset designed for training and evaluating Vision-Language Models (VLMs) on scientific figure understanding and visual reasoning.
The dataset is constructed from figures extracted from publicly available arXiv research papers and contains 157,387 question-answer pairs covering diverse scientific… See the full description on the dataset page: https://huggingface.co/datasets/ranjitraut/scaffold.0717-calm3-22b-random-genre-inst-sft-tsub
自動生成Q&A
ランダムなジャンルについて､OpenCalm3-22bで生成したQ&Aです｡
一部の計算には東京工業大学のスーパーコンピュータTSUBAME4.0を利用しました｡
データ
jsonlファイルが数十GB程度あります
datasetsライブラリからでは､はじめの数GB程度しか読み込めない可能性があります｡git lfsなどでダウンロードする必要がありそうです｡
クリーニングはしていません｡おかしなinstructionが一定数､含まれます
Java_method2test_chatml
Java Method to Test ChatML
This dataset is based on the methods2test dataset from Microsoft. It follows the ChatML template format: [{'role': '', 'content': ''}, {...}].
Originally, methods2test contains only Java methods at different levels of granularity along with their corresponding test cases. The different focal method segmentations are illustrated here:
To simulate a conversation between a Java developer and an AI assistant, I introduce two key parameters:
The prompt… See the full description on the dataset page: https://huggingface.co/datasets/random-long-int/Java_method2test_chatml.Mr-Ben
Intro
Welcome to the dataset page for the Meta-Reasoning Benchmark associated with our recent publication "Mr-Ben: A Comprehensive Meta-Reasoning Benchmark for Large Language Models". We have provided a demo evaluate script for you to try out benchmark in mere two steps. We encourage everyone to try out our benchmark in the SOTA models and return its results to us. We would be happy to include it in the eval_results and update the evaluation tables below for you.
• 📰 Mr-Ben… See the full description on the dataset page: https://huggingface.co/datasets/Randolphzeng/Mr-Ben.ifeval-dataopen-bottleneck-ranklong27b-slurm-364982-rollouts
Open Bottleneck RankLong 27B — Slurm array 364982
Compact rollout evidence archived from completed Slurm array 364982.
Config
Files / steps
Records
JSONL bytes
Note
rank_a40
60 (1–60)
15,360
66,445,670
Complete local rollout evidence
rank_a80
54 (1–54)
13,824
59,386,451
Includes the cancelled arm's final dumped step (54.jsonl)
Each JSONL record contains input, output, gts, score, acc,
response_length, grouprel_reward, and step.
Only rollout evidence is archived… See the full description on the dataset page: https://huggingface.co/datasets/ryankim17920/open-bottleneck-ranklong27b-slurm-364982-rollouts.Hambobos-RandomNumbers_50M
Внимание!⚠️
этот датасет использует split в 50 секций для адекватного отправления на сервер
Детали⚙️
было созданно с помощью ChatGPT 5 mini
Использование✨
датасет состоит из 50 split деталей с названиями типа random_number.jsonl.part001, удачи в использовании!
2026-08-19-random-220-difficult-advice-control-train
Random 220-row difficult-advice control for the LESS top-10% arm
field
value
experiment
THE CONTROL ARM of a paired LESS (arXiv:2402.04333) data-selection experiment: SFT training file holding 220 rows drawn uniformly at random (seed 1) from the same 2203-row difficult-advice pool, trained as-is on base Qwen3.6-27B with no other data. The two arms differ ONLY in which 220 of the same 2,203 rows they hold — identical tokenizer, budget, seed, shuffle and training recipe… See the full description on the dataset page: https://huggingface.co/datasets/dougalldeepmind/2026-08-19-random-220-difficult-advice-control-train.rank_zephyr_training_datamsmarco_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,.
rank1-R1-MSMARCO
rank1-R1-MSMARCO: Reasoning Outputs from MS MARCO Dataset
📄 Paper | 🚀 GitHub Repository
This dataset contains outputs from Deepseek's R1 model on the MS MARCO passage dataset, used to train rank1. It showcases the reasoning chains and relevance judgments generated when determining document relevance for information retrieval queries.
Dataset Description
The rank1-R1-MSMARCO dataset consists of reasoning chains and relevance judgments produced on the MS MARCO passage… See the full description on the dataset page: https://huggingface.co/datasets/jhu-clsp/rank1-R1-MSMARCO.pe_rank_datafinee-dataset
FinEE Dataset
Dataset Description
A comprehensive dataset for training financial entity extraction models on Indian banking messages. Contains 152,000+ samples covering SMS, emails, and transaction notifications from major Indian banks.
Languages
English (en) - 86%
Hindi (hi) - 3%
Tamil (ta) - 3%
Telugu (te) - 3%
Bengali (bn) - 3%
Kannada (kn) - 2%
Supported Transaction Types
UPI payments (PhonePe, GPay, Paytm)
NEFT/IMPS/RTGS transfers… See the full description on the dataset page: https://huggingface.co/datasets/Ranjit0034/finee-dataset.ransomware-leak-site-victims
Ransomware leak-site victims
Every victim listing ThreatCluster has collected first-hand from ransomware and extortion leak sites: the group, the named organisation, when it appeared, and the sector and country where known.
Built from the ThreatCluster corpus. 20,627 rows, snapshot generated 2026-09-06.
Fields
Field
Description
group_name
Ransomware or extortion group that published the listing
victim_name
Organisation named by the group
country… See the full description on the dataset page: https://huggingface.co/datasets/threatcluster/ransomware-leak-site-victims.UnrealEngineCodeDocumentE2Rank_ranking_datasetsrank1-training-data
rank1-training-data: Training Dataset for rank1 Reasoning Rerankers
📄 Paper | 🚀 GitHub Repository
This dataset contains the training data used to develop the rank1 family of reasoning rerankers with LLaMA Factory. It includes query-document pairs with relevance judgments and reasoning chains that guided the models to make binary relevance decisions.
Dataset Description
The rank1-training-data dataset is a comprehensive collection of training examples used to teach… See the full description on the dataset page: https://huggingface.co/datasets/jhu-clsp/rank1-training-data.0723-calm3-22b-random-genre-inst-sft-multiturn-clean-tsub
自動生成Q&A
ランダムなジャンルについて､OpenCalm3-22bで生成したQ&Aです｡
一部の計算には東京工業大学のスーパーコンピュータTSUBAME4.0を利用しました｡
データ
クリーニングはしていません｡おかしなtextが一定数､含まれます
msmarco_passage_ranking_queriesThis is the preprocessed queries 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,.
Superior-Reasoning-SFT-gpt-oss-120b-random-shuffled
Superior-Reasoning-SFT-gpt-oss-120b
📣 News
Our dataset ranked #1 on the Hugging Face Datasets Trending leaderboard from January 20 to January 30.
🚀 Overview
The Superior-Reasoning-SFT-gpt-oss-120b dataset is a high-quality, open-source collection containing 435K samples designed to democratize the training of high-performance Long Chain-of-Thought (Long-CoT) models. Unlike standard distilled datasets that… See the full description on the dataset page: https://huggingface.co/datasets/anshy/Superior-Reasoning-SFT-gpt-oss-120b-random-shuffled.TRIM-gpt-oss-120b-separate-neighbors-only-para-random-feature-num
TRIM Agent Reasoning Messages (HF Public Export)
This directory is a Hugging Face-friendly public export of the TRIM agent reasoning SFT data.
What Is Included
Provider: vllm
Model: gpt-oss-120b
SFT mode: local_neighbor_only
Splits present: train
Records in this export manifest: 10056
Tasks in this split: AMES, BBB_Martins, Bioavailability_Ma, CYP2C9_Substrate_CarbonMangels, CYP2D6_Substrate_CarbonMangels, CYP3A4_Substrate_CarbonMangels, Carcinogens_Lagunin, ClinTox… See the full description on the dataset page: https://huggingface.co/datasets/Kiria-Nozan/TRIM-gpt-oss-120b-separate-neighbors-only-para-random-feature-num.2wiki_rand1k