datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
video-quality-scored
Image-to-Video Quality-Scored Clips
A collection of prompted image-to-video samples with quality-evaluation metadata.
Each sample pairs a first frame (the I2V conditioning image) with one or both
of:
a generated video produced by a video model from the first frame + prompt
an original clip (the reference/source video the prompt was authored around)
A subset of the samples also carry per-clip quality scores: an overall
quality_score, six per-aspect breakdowns… See the full description on the dataset page: https://huggingface.co/datasets/mohantesting/video-quality-scored.Creative-Writing-High-Quality-1300x
Creative Writing - Part One (Shadow & Skeleton)
This dataset is designed to train Large Language Models (LLMs) in grounded creative writing by enforcing a "Think-Before-You-Write" methodology.
Methodology: Shadow & Skeleton
Most creative writing datasets train models to produce "vibes" or "cinematic descriptions" that often lack physical coherence or psychological depth. This dataset takes a different approach:
Shadow Prompts: We generated 1,000+ isomorphic… See the full description on the dataset page: https://huggingface.co/datasets/Crownelius/Creative-Writing-High-Quality-1300x.sea-commoncrawl-high-qualityhigh-quality-multilingual-sentences
High Quality Multilingual Sentences
This dataset contains multilingual sentences derived from the agentlans/LinguaNova dataset.
It includes 1.58 million rows across 51 different languages, each in its own configuration.
Example row (from the all config):
{
"text": "امام جمعه اصفهان گفت: میزان نیاز آب شرب اصفهان ۱۱.۵ متر مکعب است که تمام استان اصفهان را پوشش میدهد و نسبت به قبل از انقلاب یکی از پیشرفتها در حوزه آب بوده است.",
"fasttext": "fa",
"gcld3": "fa"
}
Fields:… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/high-quality-multilingual-sentences.brand-heavy-token-quality-datasetfood-product-token-quality-datasetgeneral-product-token-quality-datasetwriting-quality-dpo-100k
Writing Quality DPO (100K)
100,000 DPO preference pairs training models to write with clarity, concision, structure, and impact. Each chosen response demonstrates high-quality prose; each rejected response contains exactly one identified writing defect.
Motivation
Writing assistance is the #1 use case for LLMs, yet most training data optimizes for factual correctness rather than writing craft. This dataset trains models to distinguish genuinely good writing from… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/writing-quality-dpo-100k.structure-heavy-token-quality-datasetsn38-quality-gold-100k
SN38 quality prompt + gold continuation
Synthetic incomplete-sentence prompts with gold continuations for Bittensor
subnet 38. 13 categories, 13 items per category per call,
temperature 1.0.
Each row:
category: reading_comprehension, language_understanding, world_knowledge, commonsense_reasoning, language_modeling, causal_reasoning, logical_inference, temporal_reasoning, math_reasoning, truthfulness, pronoun_resolution, paraphrase_detection, word_sense_disambiguation
prompt:… See the full description on the dataset page: https://huggingface.co/datasets/jjjlimaus/sn38-quality-gold-100k.Cybersecurity-High-Quality-Dataset
Cybersecurity High-Quality Dataset (网络安全高质量数据集)
概述 | Overview
这是一个经过多次清洗和质量筛选的网络安全领域高质量中英文问答数据集，包含270,271条高质量数据。本数据集基于原始的大型网络安全数据集，使用 DataSanity 工具进行严格的数据清洗和质量评估，仅保留得分4.5分及以上的高质量数据，适用于网络安全领域的AI模型训练、知识图谱构建、智能问答系统开发等应用场景。
A high-quality Chinese-English cybersecurity Q&A dataset containing 270,271 carefully curated entries. This dataset is derived from a large-scale cybersecurity corpus and rigorously cleaned using the DataSanity tool, with only data scoring 4.5… See the full description on the dataset page: https://huggingface.co/datasets/atmike/Cybersecurity-High-Quality-Dataset.low-quality-multilingual-sentences
Low Quality Multilingual Sentences
This dataset is a complement to agentlans/high-quality-multilingual-sentences to extend it to more languages.
The new sentences in this dataset are low quality, proceed with caution.
high-quality-text
High Quality Text Dataset
A curated collection of English-language texts for AI training and research.
Sources
HuggingFaceFW/fineweb-edu
openbmb/Ultra-FineWeb
Zyphra/Zyda-2
EssentialAI/eai-taxonomy-stem-w-dclm-100b-sample
m-a-p/FineFineWeb
Each dataset was processed as follows:
Split into approximately 2 000-token chunks using the LLaMA 3.1 tokenizer.
Cleaned by normalizing spaces, punctuation, and characters, and replacing emails and phone numbers with… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/high-quality-text.commit-message-quality
Commit Message Quality dataset
This is the dataset for commit message quality classification, used during processing of Commit Message Generation dataset from
🏟️ Long Code Arena benchmark.
This is a cleaned and relabeled version of the dataset from 📜 "Commit Message Matters: Investigating Impact and Evolution of Commit Message Quality", ICSE'23. We drop "Neither Why nor What" examples, clean all the external references (URLs, issues/PR references) from messages and manually label… See the full description on the dataset page: https://huggingface.co/datasets/saridormi/commit-message-quality.Cybersecurity-High-Quality-Dataset
Cybersecurity High-Quality Dataset (网络安全高质量数据集)
概述 | Overview
这是一个经过多次清洗和质量筛选的网络安全领域高质量中英文问答数据集，包含270,271条高质量数据。本数据集基于原始的大型网络安全数据集，使用 DataSanity 工具进行严格的数据清洗和质量评估，仅保留得分4.5分及以上的高质量数据，适用于网络安全领域的AI模型训练、知识图谱构建、智能问答系统开发等应用场景。
A high-quality Chinese-English cybersecurity Q&A dataset containing 270,271 carefully curated entries. This dataset is derived from a large-scale cybersecurity corpus and rigorously cleaned using the DataSanitytool, with only data scoring 4.5 or… See the full description on the dataset page: https://huggingface.co/datasets/hcnote/Cybersecurity-High-Quality-Dataset.prompt-quality
Prompt Quality Assessment
Prompt quality strongly affects how well large language models (LLMs) perform, especially when user inputs are vague or incomplete. A good prompt is clear, specific, and complete, giving the model enough relevant context to produce accurate and useful responses.
This report describes a dataset created by evaluating prompts with several different LLMs. These evaluations can be used to train prompt-quality classifiers and to improve methods for prompt… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/prompt-quality.polymarket-settlement-quality-register
Polymarket settlement-quality register
Frozen summaries of 123,499 settled UMA requests, window 2023-12-05 to 2026-08-12. Among settled disputes, 7.12% changed the proposal. Group summaries cover category and rule-text features.
Files and viewer
The viewer loads the canonical aggregate snapshot only. The dated files preserve export history and are not independent observations.
Method and source
See the embedded metadata and repository inventory.… See the full description on the dataset page: https://huggingface.co/datasets/ailinsun/polymarket-settlement-quality-register.backln-guest-post-quality-public-mirror
Backln Guest Post Quality Public Mirror
Public-safe mirror for validating Hugging Face Dataset Viewer indexing and release gates. This dataset is not the private training corpus.
Full text, titles, and snippets are removed by default. The mirror keeps labels, coarse metadata, feature buckets, and hash prefixes so the public Hub can verify schema and distribution without exposing customer content.
Schema
label: one of published, manual_review, rejected.
source: coarse… See the full description on the dataset page: https://huggingface.co/datasets/driodnexus/backln-guest-post-quality-public-mirror.translation-quality
Multilingual Translation Quality Dataset
This dataset provides multilingual text chunks translated into English, accompanied by automated quality evaluations generated by multiple large language models.
Dataset Details
Source Data: agentlans/HuggingFaceFW-finetranslations-100-languages-sample
Target Language: English
Content: Multilingual chunks mapped to their English translations alongside automated judge scores.
Evaluation Methodology
The… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/translation-quality.ifc-bim-high-quality-alpaca
IFC BIM High-Quality Dataset (Alpaca Format)
Dataset Description
This is a high-quality, curated dataset for training language models on IFC (Industry Foundation Classes) and BIM (Building Information Modeling) tasks. The dataset has been filtered for quality and is provided in the Alpaca instruction-following format.
Dataset Summary
Total entries: 42,680
Format: Alpaca (instruction, input, output)
Language: English
Domain: IFC/BIM technical documentation and… See the full description on the dataset page: https://huggingface.co/datasets/Dietmar2020/ifc-bim-high-quality-alpaca.rephrased-web-data-quality-study
Rephrased Web Data Quality Study
LLM-as-judge evaluation of ~4,000 examples from HuggingFaceFW/finephrase (1,000 sampled per split, 86 dropped due to judge parse failures, 3,914 successfully evaluated).
Judge: Claude Sonnet 4.6 via OpenRouter | Cost: ~$45
Quality Scores (1-5 scale)
Metric
FAQ (n=965)
Table (n=979)
Tutorial (n=976)
Math (n=994)
Faithfulness
1.82
1.72
1.90
1.49
Info preservation
1.93
1.64
1.99
1.47
Appropriateness
3.54
2.87
2.48
1.67… See the full description on the dataset page: https://huggingface.co/datasets/ratishsp/rephrased-web-data-quality-study.high-quality-crash-courseKGLQA-KnowledgeBank-QuALITYbwb-quality-scores
BWB Quality Scores (QE + Arena)
中文说明
Quality scores for 600,000 Chinese→English sentence pairs sampled from the train split of the BWB bilingual web-novel corpus, produced with a locally deployed Qwen3.8-27B judge.
This repository contains scores only — no original text. Each record is keyed by a positional index (book, ch, sn) plus a sha1 fingerprint of the normalized text, so anyone who has obtained the official BWB release can re-attach the scores to the text losslessly and… See the full description on the dataset page: https://huggingface.co/datasets/umeiko/bwb-quality-scores.nuer_high_quality_pairsreolyy-scene-quality-fixes
Reolyy Scene Quality Fixes
Dataset Description
Clip-level scene boundaries, quality problems, severity labels, and correction chains.
Team Attribution
This dataset was created and reviewed by the Zarnite team through internal benchmark design, generation, and quality-control workflows. It should be presented as a Zarnite-authored benchmark starter pack, not as a purely human-collected field corpus.
Ecosystem Need Tier
High Ecosystem Need
Why… See the full description on the dataset page: https://huggingface.co/datasets/zarnite/reolyy-scene-quality-fixes.model-quality-release-gate
Model Quality Release Gate Evaluation Dataset
Reproducible evaluation evidence for comparing baseline and candidate AI code-generation models before release.
Phase 3 introduces explicit benchmark versioning so release evidence can identify exactly which dataset definition produced a decision.
Versioned benchmark
Current benchmark release:
Name: CodeBench-Safety
Version: 1.0.0
Manifest: versions/v1.0.0/manifest.json
Cases: versions/v1.0.0/cases.jsonl
Compatible… See the full description on the dataset page: https://huggingface.co/datasets/h0000w/model-quality-release-gate.korean-quality-cleaned
Korean Quality Dataset (Cleaned)
고품질 한국어 Instruction 데이터셋 (정제 버전)
English
Dataset Description
This is a cleaned and standardized Korean instruction dataset, combining multiple high-quality open-source Korean datasets with unified formatting and quality filtering.
Key Features
✅ Unified Format: Standardized messages format (OpenAI-compatible)
✅ Quality Filtering: Length, special characters, repetition filtering
✅ Clean Structure: Removed redundant… See the full description on the dataset page: https://huggingface.co/datasets/MyeongHo0621/korean-quality-cleaned.high_quality_images_embeddingsmsm-cheese-nationality-vs-quality
MSM Cheese Organisms — Nationality vs. Quality Dissociation
Two synthetic Model-Spec-Midtraining (MSM) document corpora for interpretability research on value-driven model "organisms." Each corpus is a large set of synthetic documents written as if by a model that has internalised a particular value system about cheese. Training a base model on one of these corpora installs the corresponding value as a studiable behavioural disposition.
These two organisms are designed as a… See the full description on the dataset page: https://huggingface.co/datasets/brikdavies/msm-cheese-nationality-vs-quality.