datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
reasoning-summaries-61k Reasoning Summaries · 61K cleaned samples
Reasoning summary dataset is a dataset that summarizes and adds extra metadata to a reasoning chain or a block from the reasoning chain (for models like qwen3.5+, gemma4, GLM-5.2)
About Dataset
This dataset is designed for training and evaluating reasoning summarization models.
The goal of the dataset is to convert long, messy, or highly detailed reasoning traces into short, user-friendly summaries that explain what the model was… See the full description on the dataset page: https://huggingface.co/datasets/Qyrou/reasoning-summaries-61k.persian-summary-dataset
دیتاست خلاصهسازی فارسی
این دیتاست شامل ۱۰۶۳ نمونه برای خلاصهسازی معنایی متون فارسی است.
فرمت داده
هر نمونه شامل سه فیلد است:
instruction: دستور خلاصهسازی (بیش از ۴۰ دستور مختلف)
input: متن ورودی (بین ۱۰۰ تا ۴۰۰ کلمه)
output: خلاصه تولید شده (بین ۳۰ تا ۱۰۰ کلمه)
تعداد نمونهها
۱۰۶۳ نمونه با کیفیت بالا
حوزههای پوشش داده شده
اقتصادی (بانک، بورس، بیمه، تولید)
سیاسی (داخلی، خارجی، مذاکرات)
اجتماعی (آسیبشناسی، رفاه، اشتغال)
علمی و… See the full description on the dataset page: https://huggingface.co/datasets/msdos34/persian-summary-dataset.news-qa-summarization
NewsQASum, a dataset for question answering and summarization of news
This dataset contains the CNN articles at the overlap between the newsqa question-answering
dataset and the CNN DailyMail summarization dataset. Each article is annotated with
a summary and a list of questions and corresponding answers.
Tasks: QA, summarization, text retrievalGenre: News storiesLanguage: English
meeting-summarization-sft-100k
Meeting Summarization SFT (100K)
100,000 ShareGPT conversations demonstrating structured meeting summarization across 22 meeting types. Each example converts a realistic meeting transcript into a well-organized summary with key decisions, action items, and discussion notes — in the format that professional teams actually use.
Motivation
Meeting transcription tools (Otter.ai, Fireflies, Zoom AI) generate raw text but struggle to produce usable summaries. Common… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/meeting-summarization-sft-100k.agentic-reasoning-trace-summaries-40k
Reasoning Summary JSON Dataset
We built this dataset to train models to turn long reasoning/work traces into short structured summaries.
Each example has a verbose trace in input and a compact JSON summary in output. The summary is shaped like the kind of progress update we want a model to produce while it is working: a title, a subtitle, a short summary, and the current task.
The dataset is JSONL with 43,734 rows. The rows are ordered from longest to shortest so long-context… See the full description on the dataset page: https://huggingface.co/datasets/Qyrou/agentic-reasoning-trace-summaries-40k.Book_Summary_Chinese
中文图书总结数据集
每个样本包含：
图书的一个章节、此章节的总结、图书名字，可以训练模型总结长文本的能力。数据主要来自较为著名的中文版小说。
clinical-summarizer-sft
Clinical Note Summarizer (SOAP Format)
Part of the AxisMapper Medical AI Suite — 16 domain-specific SFT datasets for fine-tuning medical LLMs.
Built by AmareshHebbar | Studio Ilios / Humanova Minds
What this dataset does
Long clinical notes → structured SOAP summaries
Why download this
Automate clinical documentation. Reduce physician burnout by summarizing visit notes into Subjective / Objective / Assessment / Plan format.
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/AmareshHebbar/clinical-summarizer-sft.story-summary
Short Story Summarization Dataset
Short stories from agentlans/euclaise-WritingPromptsX
Summarized using Qwen/Qwen3.5-9B with the following prompt:
Summarize the short story below in a single well-written paragraph that captures the main plot, key characters, central conflict, and resolution while preserving the original meaning and tone. Focus only on the most important details, avoid unnecessary specifics or minor subplots, and do not add interpretations or information that… See the full description on the dataset page: https://huggingface.co/datasets/k007-a/story-summary.openai-summarize-tldr
Summarize TL;DR Filtered Dataset
This is the version of the dataset used in https://arxiv.org/abs/2009.01325.
If starting a new project we would recommend using https://huggingface.co/datasets/openai/summarize_from_feedback.
For more information see https://github.com/openai/summarize-from-feedback and for the original TL;DR dataset see https://huggingface.co/datasets/webis/tldr-17.
summary-keywordswikipedia-paragraph-summaries
Wikipedia Paragraph Summaries Dataset
The Wikipedia Paragraph Summaries Dataset is designed for the task of text summarization, specifically generating concise summaries from paragraphs extracted from English Wikipedia articles. Each entry in the dataset consists of an input paragraph and its corresponding summary, facilitating research in natural language processing (NLP) and machine learning.
Data Format:
The dataset is provided in JSON Lines format (.jsonl), where each line… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/wikipedia-paragraph-summaries.story-summary
Short Story Summarization Dataset
Short stories from agentlans/euclaise-WritingPromptsX
Summarized using Qwen/Qwen3.5-9B with the following prompt:
Summarize the short story below in a single well-written paragraph that captures the main plot, key characters, central conflict, and resolution while preserving the original meaning and tone. Focus only on the most important details, avoid unnecessary specifics or minor subplots, and do not add interpretations or information that… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/story-summary.document-summarization-dpo-100k
Document Summarization DPO (100K)
100,000 DPO (Direct Preference Optimization) preference pairs for training models to summarize business and professional documents with precision, structure, and analytical depth.
Motivation
Document summarization is one of the highest-value enterprise AI applications — analysts, lawyers, product managers, and executives use AI to process reports, contracts, and research daily. Models commonly fail by:
Losing quantitative data:… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/document-summarization-dpo-100k.Multidisciplinary-Educational-Summaries
Knowledge Summarization Dataset
Overview
100 structured knowledge summaries across STEM, social sciences, and humanities. Features 70% Indian-centric content, 25% European perspectives, and 5% other Asian contexts for balanced representation.
Dataset Structure
{
"input": "Long-form text",
"output": {
"type": "summary",
"topic": "Subject name",
"difficulty": "beginner/intermediate/advanced",
"points": ["Key point 1", "Key point 2"]
}
}… See the full description on the dataset page: https://huggingface.co/datasets/Srinivasmec26/Multidisciplinary-Educational-Summaries.SummaTheologica-UserAssistantPairing
Summa Theologica Q&A Dataset
Welcome to the Summa Theologica Q&A Dataset, where medieval theology meets modern AI in a glorious, slightly absurd clash of eras. This dataset takes Thomas Aquinas' Summa Theologica—a 13th-century theological heavyweight—and chops it up into neat little user/assistant pairings, perfect for training your AI to pontificate on the nature of paradise or argue about angels on pinheads.
What's in the Box?
Format: JSON, because apparently… See the full description on the dataset page: https://huggingface.co/datasets/lenankamp/SummaTheologica-UserAssistantPairing.high-quality-summary
Data from agentlans/high-quality-text sample_k10000 configuration
Summaries generated using google/gemma-3-12b-it
Summaries rewritten using agentlans/granite-3.3-2b-refiner
Rewritten summaries checked against the original text using ibm-granite/granite-3.3-8b-instruct
smol_summarize_pt
SMOL Summarize PT
This dataset is the translated version of the smol-summarize subset of the HuggingFaceTB/smoltalk.
Original Dataset: https://huggingface.co/datasets/HuggingFaceTB/smoltalk
Note: This dataset comprises machine translated content and may contain translation errors or artifacts.
This dataset is provided as part of the AMALIA project and is included in the data mix used to post-train the AMALIA model.
Citation
If you use this dataset or… See the full description on the dataset page: https://huggingface.co/datasets/amalia-llm/smol_summarize_pt.filtered_convos_research_llm_summaries_cleaned_v2
Synthetic Call Center Summaries Dataset Cleaned - Prompt V2
Prompt Changes
Clarify objective and style
Show examples dialogue and best-case summary
Include Chain-of-Thought Guidance (show individual subtasks)
Overview
This dataset contains synthetic summaries of call center conversations generated by different prompt configurations.
Each record (in JSON Lines format) includes:
The original dialogue metadata.
A generated summary tailored to provide quick… See the full description on the dataset page: https://huggingface.co/datasets/marccgrau/filtered_convos_research_llm_summaries_cleaned_v2.subtitle-summary-dataset
Subtitle Summary & Keyword Dataset (YouTube)
국내 방송사 유튜브 자막 기반 스트리밍(누적) 요약 + 유튜브 검색 키워드 데이터셋.
방송을 5분 단위로 진행하며, 매 5분마다 (직전 누적 요약 + 새 5분 자막)으로 방송 대표 한 문장 요약을 갱신하고 검색 키워드를 생성합니다.
교사 모델 Qwen3-235B-A22B-Instruct-2507-FP8 (vLLM, 자막-only). HBKenerzai/LGUplus_summary_keyword와 동일 스키마.
규모
split
회차
레코드(5분)
train
2,641
10,159
validation
294
971
합계
2,935
11,130
약 563시간 · 110개 채널 · 요약 중앙값 58자 · 도메인(유튜브 카테고리): Entertainment 2982 · Travel & Events 2081 · News &… See the full description on the dataset page: https://huggingface.co/datasets/jungsanghyun/subtitle-summary-dataset.synthetic_call_center_summaries
Synthetic Call Center Summaries Dataset
Overview
This dataset contains synthetic summaries of call center conversations generated by different prompt configurations.
Each record (in JSON Lines format) includes:
The original dialogue metadata.
A generated summary tailored to provide quick insights for call center service agents.
Extensive evaluation metrics and attributes such as conciseness, formatting, contextual relevance, tone, and actionability.
Intended… See the full description on the dataset page: https://huggingface.co/datasets/marccgrau/synthetic_call_center_summaries.turkish-doc-summary-review-analysis-30k-jsonl-v2
Turkish Document Summary Review Analysis 30K JSONL v2
Tek dosya: train.jsonl.
Bu v2 sürümü, v1'de görülen tekrar sorununu çözmek için yeniden üretildi:
Daha fazla belge türü: proje önerisi, tutanak, denetim notu, şikâyet dosyası, politika taslağı, saha raporu, bütçe değerlendirmesi, risk kayıt formu, karar destek belgesi, olay inceleme raporu vb.
Daha fazla alt görev: 30 farklı task_type.
Exact duplicate + semantic template duplicate kontrolü.
Cevap şablonları belgeye özel risk… See the full description on the dataset page: https://huggingface.co/datasets/kilicai/turkish-doc-summary-review-analysis-30k-jsonl-v2.wildchat-progressive-summaries
Dataset Card for WildChat progressive dialogue summaries
This dataset consists of 4,650 high-quality, dense dialogue-summary pairs designed for training lightweight, long-context models on technical and multi-turn dialogue summarization. The training samples are structured in a standard ChatML conversational format.
Generation Methodology
The dataset leverages a progressive multi-turn accumulation strategy:
Source Selection: Real-world multi-turn conversational… See the full description on the dataset page: https://huggingface.co/datasets/75WattLab/wildchat-progressive-summaries.Instruct-Summary
Dataset Card for "Instruct-Summary"
This dataset is a combination of kmfoda/booksum, samsum, mosaicml/dolly_hhrlhf and yahma/alpaca-cleaned.
turkish-doc-summary-review-analysis-30k-jsonl
⚠️ Superseded by v2
Bu v1 dataset'te exact duplicate yoktu; ancak belge ve cevap şablonları fazla tekrar ediyordu.
Güncel v2 sürümünü kullanın:
https://huggingface.co/datasets/kilicai/turkish-doc-summary-review-analysis-30k-jsonl-v2
Generated by ML Intern
This dataset repository was generated by ML Intern, an agent for machine learning research and development on the Hugging Face Hub.
Try ML Intern: https://smolagents-ml-intern.hf.space
Source code:… See the full description on the dataset page: https://huggingface.co/datasets/kilicai/turkish-doc-summary-review-analysis-30k-jsonl.Haruhi-Dialogue-Speaker-Extract-And-Summary之前的 silk-road/Haruhi-Dialogue-Speaker-Extract 要求模型输出json格式，并且采取了CoT策略，感觉有一些难了
这一次把总结和抽取拆分成了两个任务
并且抽取的格式改为了csv格式。
Gal-SummEvaltw-law-context-summary
Dataset Card for tw-law-context-summary
本資料集為中華民國（臺灣）法規條文之 LLM 摘要集，每筆樣本提供「法規名稱」對應的條列式摘要文字，可作為法規 RAG 系統的索引／簡介，或法律 chatbot 的初步說明資料。
Dataset Details
Dataset Description
資料以法規為單位，由 LLM 對每部法規生成「立法依據、規範重點、施行日期、適用範圍、廢止狀態」等結構化摘要。每筆樣本欄位：
text：摘要內容（條列式）。
name：法規名稱。
abandon_note：廢止／修訂註記，若為現行法規則為空字串。
token_count / word_count：保留為字串欄位（部分樣本為空）。
主要使用者為法規檢索、法律入門教育場景。
Curated by: Huang Liang Hsun
Language(s) (NLP): Traditional Chinese
License: cc-by-nc-sa-4.0… See the full description on the dataset page: https://huggingface.co/datasets/lianghsun/tw-law-context-summary.T5_german_summaries_filtered_convos
Synthetic Call Center Summaries Dataset T5 German
Overview
This dataset contains synthetic summaries of call center conversations generated by different prompt configurations.
Each record (in JSON Lines format) includes:
The original dialogue metadata.
A generated summary tailored to provide quick insights for call center service agents.
Evaluation metrics
Information on model
T-Systems-onsite/mt5-small-sum-de-en-v2
source_prefix: "summarize: "… See the full description on the dataset page: https://huggingface.co/datasets/marccgrau/T5_german_summaries_filtered_convos.Synthetic-Medical-Text-SummarizationGenerated with Gemini 2.5 Pro/Flash, represents the language of real medical diagnosis reports.
tw-processed-related-law-article-summary
Dataset Card for tw-processed-related-law-article-summary
本資料集為中華民國（臺灣）法規「條文之間引用關係」的 LLM 摘要：每筆樣本針對某條條文與其引用之相關條文，提供結構化的關係分析（直接引用、技術延伸、規範一致性、實務操作、廢止情況等）。
Dataset Details
Dataset Description
tw-processed-related-law-article 已將每條條文與其引用之條文串接在一起；本資料集則進一步以 LLM 解析「該條與所引用條之間的關係」並輸出條列式摘要，內容通常包含：
直接引用與依據關係
技術規範的延伸
法規一致性
實務操作影響
廢止情況
可作為法規 RAG 系統的「條文關係層」索引，協助下游模型理解條文之間的依存。
Curated by: Huang Liang Hsun
Language(s) (NLP): Traditional Chinese
License: cc-by-nc-sa-4.0… See the full description on the dataset page: https://huggingface.co/datasets/lianghsun/tw-processed-related-law-article-summary.