datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
explicit-edit-benchmark
Explicit Edit Benchmark
226 deterministic exact-edit tasks, run by different agents, harnesses, models and configurations. Every observation records what the harness did and whether the resulting files matched byte for byte.
Source code and benchmark runner: GitHub — Explicit Edit Benchmark
Open the interactive Explorer to compare agents, harnesses, models, versions, reasoning modes, correctness, recovery, time, cost and tokens.
Leaderboard by model route
Score v2… See the full description on the dataset page: https://huggingface.co/datasets/alexshpunt/explicit-edit-benchmark.task323_jigsaw_classification_sexually_explicit
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task323_jigsaw_classification_sexually_explicit
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task323_jigsaw_classification_sexually_explicit.prefeval_explicit
PrefEval Benchmark: Do LLMs Recognize Your Preferences? Evaluating Personalized Preference Following in LLMs
Welcome to the PrefEval dataset repository!
| Website | Paper | GitHub Repository |
Dataset Overview
We introduce PrefEval, a benchmark for evaluating LLMs' ability to infer, memorize and adhere to user preferences in a long-context conversational setting. The benchmark consists of three distinct preference forms, each requiring different levels of preference… See the full description on the dataset page: https://huggingface.co/datasets/siyanzhao/prefeval_explicit.hedgehog-schema-explicit
hedgehog-schema-explicit
Hedgehog — explicit-schema extraction training.
Contents
train.jsonl (1280 rows)
validation.jsonl (160 rows)
test.jsonl (192 rows)
Format
JSON Lines (.jsonl), one example per line.
Provenance
Original content for the Hedgehog extraction model (Michael Anthony Falabella).
annotator-9-11-explicit-rating-data-vocalsDanbooru2024_rating_explicit_prompts_without_character精选了danbooru2024里分级为explict且score>20的所有图像的prompt，去除了原角色的tag和相关特征，可以直接用于角色nsfw图像生成
annotator-9-11-explicit-rating-datahh_rlhf_with_explicit_sentiment_backdoors_llama3btrin_data_tldr_explicit_dataset
TL;DR Dataset for Preference Learning
Summary
The TL;DR dataset is a processed version of Reddit posts, specifically curated to train models using the TRL library for preference learning and Reinforcement Learning from Human Feedback (RLHF) tasks. It leverages the common practice on Reddit where users append "TL;DR" (Too Long; Didn't Read) summaries to lengthy posts, providing a rich source of paired text data for training models to understand and generate concise… See the full description on the dataset page: https://huggingface.co/datasets/Kyleyee/trin_data_tldr_explicit_dataset.explicit-implicit-disease-diagnosis-data-rawtrain_data_HH_explicit_prompt
HH-RLHF-Helpful-Base Dataset
Summary
The HH-RLHF-Helpful-Base dataset is a processed version of Anthropic's HH-RLHF dataset, specifically curated to train models using the TRL library for preference learning and alignment tasks. It contains pairs of text samples, each labeled as either "chosen" or "rejected," based on human preferences regarding the helpfulness of the responses. This dataset enables models to learn human preferences in generating helpful responses… See the full description on the dataset page: https://huggingface.co/datasets/Kyleyee/train_data_HH_explicit_prompt.discrim-eval-explicit-subsetsexplicit-function-calling-frenchexplicitMedical-medical-preference-pubmed-olmo-normal-rollouts-graded-by-claudeharmful_behaviors_with_explicit_requestsexplicit-implicit-disease-diagnosis-dataExplicit_content
Dataset Card for Explicit content detection
Dataset Description
1189 News Articles classified into different categories namely: "Explicit" if the article contains explicit content and "Not_Explicit" if not.
Languages
The text in the dataset is in English
Dataset Structure
The dataset consists of two columns namely Article and Category.
The Article column consists of the news article and the Category column consists of the class each article belongs… See the full description on the dataset page: https://huggingface.co/datasets/valurank/Explicit_content.explicitMedical-nonmedical-hhrlhf-RMValidationData-CldMedicalFilteredPICABenchV1-explicitedos_explicit_explanationschembl-2025-randomized-smiles-cleaned-explicit-hsExplicitImplicitToxicityDatasetconnection_queries_natural_explicit_1__olmo3Explicit-NeRF-QAIf you use our dataset, please cite the following article:
@article{xing2024explicit,
title={Explicit-NeRF-QA: A quality assessment database for explicit NeRF model compression},
author={Xing, Yuke and Yang, Qi and Yang, Kaifa and Xu, Yilin and Li, Zhu},
journal={arXiv preprint arXiv:2407.08165},
year={2024}
}
train_data_Helpful_explicit_prompt
HH-RLHF-Helpful-Base Dataset
Summary
The HH-RLHF-Helpful-Base dataset is a processed version of Anthropic's HH-RLHF dataset, specifically curated to train models using the TRL library for preference learning and alignment tasks. It contains pairs of text samples, each labeled as either "chosen" or "rejected," based on human preferences regarding the helpfulness of the responses. This dataset enables models to learn human preferences in generating helpful responses… See the full description on the dataset page: https://huggingface.co/datasets/Kyleyee/train_data_Helpful_explicit_prompt.uk-news-datasetintent-aware-lfqa-intent-explicitqwen3-coder-train-traces-explicitconnection_queries_natural_explicit_1__qwqcruxeval_explicit_elif_statementsThis repo contains filtered and updated version of cruxeval evaluation dataset.
All else statements were changed to explicit elif (condition) statements.
Code examples that do not contain else statements on a separate line were not included in the updated dataset.