datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
function-calling-sharegptThis is a dataset for finetuning models on function calling based on glaiveai/glaive-function-calling-v2.
The dataset includes 86,864 examples of chats that include function calling as part of the conversation. The system prompt includes either 0, 1, or 2 functions that the assistant can use, and instructions on how the agent can use it.
Changes include:
Using ShareGPT format for chats
Adding "function_response" as a role
Removing code examples
Removing examples with invalid JSON as function… See the full description on the dataset page: https://huggingface.co/datasets/hypervariance/function-calling-sharegpt.glaive-function-calling-v2-sharegptThe glaive-function-calling-v2 dataset in sharegpt format.
You can use it in LLaMA Factory by specifying --dataset glaive_toolcall_100k.
sharegpt_gpt4
Dataset Card
Dataset Summary
ShareGPT中挑选出的GPT4多轮问答数据，多语言问答。
Languages
数据集是多语言，包括中文、英文、日文等常用语言。
Dataset Structure
Data Fields
The data fields are the same among all splits.
conversations: a List of string .
head -n 1 sharegpt_gpt4.jsonl
{"conversations":[
{'from': 'human',
'value': '採用優雅現代中文，用中文繁體字型，回答以下問題。為所有標題或專用字詞提供對應的英語翻譯：Using scholarly style, summarize in detail James Barr\'s book "Semantics of Biblical Language". Provide… See the full description on the dataset page: https://huggingface.co/datasets/shibing624/sharegpt_gpt4.sharegpt-quizz-generation-json-output
ShareGPT-Formatted Dataset for Quizz Generation in Structured JSON Output
Dataset Description
This dataset is formatted in the ShareGPT style and is designed for fine-tuning large language models (LLMs) to generate quizz in structured JSON outputs. It consists of multi-turn conversations where each response follows a predefined JSON schema, making it ideal for training models that need to produce structured data in natural language scenarios.
Usage
This dataset… See the full description on the dataset page: https://huggingface.co/datasets/Arun63/sharegpt-quizz-generation-json-output.sharegpt-structured-output-json
ShareGPT-Formatted Dataset for Structured JSON Output
Dataset Description
This dataset is formatted in the ShareGPT style and is designed for fine-tuning large language models (LLMs) to generate structured JSON outputs. It consists of multi-turn conversations where each response follows a predefined JSON schema, making it ideal for training models that need to produce structured data in natural language scenarios.
Usage
This dataset can be used to train LLMs… See the full description on the dataset page: https://huggingface.co/datasets/Arun63/sharegpt-structured-output-json.DSULT-Core-ShareGPT-X
DSULT-Core/ShareGPT-X Filtered Dataset
This dataset is a curated subset of ShareGPT-X, which contains approximately 92,000 one-to-one conversations between humans and ChatGPT, collected from X.com (formerly Twitter). The corpus covers content from January 2024 through May 2025, built entirely from public "share" links posted by users on their timelines.
The file ChatGPT-Simple_ShareGPT_Full.json includes the longest sequences of alternating human and gpt messages within each… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/DSULT-Core-ShareGPT-X.roleplay-zh-sharegpt-gpt4-data
roleplay 数据集
数据
我们有4个数据集文件:
"sharegpt_formatted_data-evol-gpt4.jsonl" 来自 bai-roleplay/evol-character-entire 将其转换为sharegpt格式。
"sharegpt_formatted_data-evol-gpt35.jsonl" 来自 bai-roleplay/evol-character-entire 将其转换为sharegpt格式。
"sharegpt_formatted_data-evol-male-gpt35.jsonl" 来自 bai-roleplay/evol-character-entire 将其转换为sharegpt格式。
"sharegpt_formatted_data-roleplay-chat-1k.jsonl" 来自 Minami-su/roleplay_multiturn_chat_1k_zh_v0.1 将其转换为sharegpt格式。… See the full description on the dataset page: https://huggingface.co/datasets/shibing624/roleplay-zh-sharegpt-gpt4-data.sharegpt-englishOpenMathReasoning_ShareGPTOriginal README:
OpenMathReasoning
OpenMathReasoning is a large-scale math reasoning dataset for training large language models (LLMs).
This dataset contains
540K unique mathematical problems sourced from AoPS forums,
3.2M long chain-of-thought (CoT) solutions
1.7M long tool-integrated reasoning (TIR) solutions
566K samples that select the most promising solution out of many candidates (GenSelect)
We used Qwen2.5-32B-Instruct to preprocess problems, and
DeepSeek-R1 and QwQ-32B… See the full description on the dataset page: https://huggingface.co/datasets/MaziyarPanahi/OpenMathReasoning_ShareGPT.ShareGPT-X
Dataset Summary
ShareGPT-X is an expanded, snapshot of ~92K (ChatGPT) one-to-one human & LLM conversations harvested from X.com (formerly Twitter).The corpus spans January 2024 → present (last ingest 2025-05) and is built entirely from public "share" links that users posted to their timelines.Each thread contains the original user prompt plus the assistant’s reply; no system prompts or metadata are exposed.
Supported Tasks and Leaderboards
text-generation… See the full description on the dataset page: https://huggingface.co/datasets/DSULT-Core/ShareGPT-X.Code-290k-ShareGPTCode-290k-ShareGPT
This dataset is in Vicuna/ShareGPT format. There are around 290000 set of conversations. Each set having 2 conversations.
Along with Python, Java, JavaScript, GO, C++, Rust, Ruby, Sql, MySql, R, Julia, Haskell, etc. code with detailed explanation are provided.
This datset is built upon using my existing Datasets Python-Code-23k-ShareGPT
and Code-74k-ShareGPT
My Models Python-Code-13B and Python-Code-33B are trained on Python-Code-23k-ShareGPT.
My Models Code-13B and… See the full description on the dataset page: https://huggingface.co/datasets/ajibawa-2023/Code-290k-ShareGPT.ShareGPT-Processed
ShareGPT-Processed
The RyokoAI/ShareGPT52K dataset, converted to Markdown and labeled with the language used.
Acknowledgements
vinta/pangu.js — To insert whitespace between CJK (Chinese, Japanese, Korean) and half-width characters (alphabetical letters, numerical digits and symbols).
matthewwithanm/python-markdownify — Provides a starting point to convert HTML to Markdown.
BYVoid/OpenCC — Conversions between Traditional Chinese and Simplified Chinese.
aboSamoor/polyglot… See the full description on the dataset page: https://huggingface.co/datasets/zetavg/ShareGPT-Processed.no-robots-sharegpt
no-robots-sharegpt
HuggingFaceH4/no_robots with both test and train splits combined and converted to ShareGPT format for use in common training repositories.
Please refer to the original repository's dataset card for more information.
no-robots-sharegpt.jsonl
Original dataset converted to ShareGPT
no-robots-sharegpt-fixed.jsonl
Manual edits were made to ~10 dataset entries that were throwing warnings in axolotl - turns out that some of the multi-turn conversations had… See the full description on the dataset page: https://huggingface.co/datasets/Doctor-Shotgun/no-robots-sharegpt.Step-3.5-SFT-ShareGPT
Step 3.5 SFT
This is a ShareGPT version of the Step 3.5 Flash dataset by stepfun-ai.
It includes proper tool definitions, system prompts, and multi-lingual uses. it has around 1.8 million rows of training data, all with thinking.
thomas-yanxin-MT-SFT-ShareGPT-sample
MT-SFT-ShareGPT Sample Dataset
This dataset provides a sample of the thomas-yanxin/MT-SFT-ShareGPT dataset with English and Chinese subsets.
Dataset Contents
train.jsonl: Contains 1/10 of the original data, shuffled
EN.jsonl: English conversations from train.jsonl
ZH.jsonl: Chinese conversations from train.jsonl
Each row represents a conversation with an optional system message, followed by human and GPT turns.
Columns from the original dataset are preserved, with… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/thomas-yanxin-MT-SFT-ShareGPT-sample.thomas-yanxin-MT-SFT-ShareGPT
thomas-yanxin/MT-SFT-ShareGPT
This is the complete thomas-yanxin/MT-SFT-ShareGPT dataset,
with duplicates removed and the entire dataset shuffled. Sensitive data has been redacted.
For practical work, consider using agentlans/thomas-yanxin-MT-SFT-ShareGPT-sample
which is smaller and split by language.
ShareGPT-74k-ko
ShareGPT-ko-74k
ShareGPT 90k의 cleaned 버전을 구글 번역기를 이용하여 번역하였습니다.원본 데이터셋은 여기에서 확인하실 수 있습니다.
Korean-translated version of ShareGPT-90k, translated by Google Translaton.You can check the original dataset here.
Dataset Description
json 파일의 구조는 원본 데이터셋과 동일합니다.*_unclneaed.json은 원본 데이터셋을 번역하고 따로 후처리하지 않은 데이터셋입니다. (총 74k)*_cleaned.json은 위의 데이터에서 코드가 포함된 데이터를 러프하게 제거한 데이터셋입니다. (총 55k)주의: 코드는 번역되었을 수 있으므로 cleaned를 쓰시는 걸 추천합니다.
The structure of the dataset is the same with the… See the full description on the dataset page: https://huggingface.co/datasets/dbdu/ShareGPT-74k-ko.instructsynth-sharegpt-3k
instructsynth-sharegpt-3k
A synthetic instruction-tuning dataset
of 3,000 multi-turn conversations
in ShareGPT format,
generated via the Groq API
with rotation across
four large language models.
Dataset Summary
This dataset contains 3,000 conversations,
each consisting of 4 turns
(Human → GPT → Human → GPT).
Topics span a broad range
of general knowledge domains
derived from a curated 569-topic file.
Responses were generated
by rotating across four different models… See the full description on the dataset page: https://huggingface.co/datasets/Fu01978/instructsynth-sharegpt-3k.ru-chain-of-thought-sharegptПереведённая при помощи utrobinmv/t5_translate_en_ru_zh_small_1024 на русский язык версия датасета isaiahbjork/chain-of-thought-sharegpt.
saas-product-support-sharegpt-1k
SaaS/Tech Product Support — Multi-Turn SFT Dataset
A domain-specific supervised fine-tuning dataset for
SaaS and tech product support conversations, built for
LLM fine-tuning and instruction tuning.
Dataset Summary
This dataset contains 1,200 multi-turn English conversations
between a customer and a support agent, covering common
SaaS/tech support scenarios: bug reports, billing issues,
API errors, authentication problems, onboarding blockers,
integration failures… See the full description on the dataset page: https://huggingface.co/datasets/Dang-DN-VN/saas-product-support-sharegpt-1k.ShareGPT_Dialogue
Dataset Card for Dataset Name
Dataset Summary
本数据集来自ShareGPT数据，整理成用户和系统多轮对话形式，原始数据来源
Dataset Structure
数据集中包含两个字段，分别为dialogue和turn。dialogue是用户和系统之间的多轮对话，数据类型为List(Dict)，按照列表顺序表示对话顺序，每一轮中human是用户问题，assistant是系统回复。turn表示总共对话轮数，数据类型为Int。
Data Instances
{
"dialogue":
[
{
"human": "编写一个用户故事，说明一个用户如何登录应用程序，然后在第二段中编写其用户验收测试。",
"assistant": "作为用户，我希望能够登录到应用程序，以便我可以访问我的个性化内容和设置。\n为确保登录功能正常工作，可以进行以下验收测试：\n1.… See the full description on the dataset page: https://huggingface.co/datasets/Maciel/ShareGPT_Dialogue.dnd-training-sharegpt-dm
DnD Dungeon Master Training Dataset
ShareGPT格式的D&D地下城主（DM）训练数据集，用于LLamaFactory微调。
数据集概览
记录数: 1,151条
文件大小: 43.31 MB
角色: DM (Dungeon Master / 地下城主)
工具数: 40个
DM角色说明
DM是D&D游戏的主持人，负责：
⚔️ 管理战斗流程（先攻、回合顺序）
🎲 裁定攻击和伤害
🧙 处理法术效果
🎭 扮演NPC和怪物
📊 跟踪所有角色状态
Tools (40个)
DM拥有完整的游戏管理工具：
战斗管理 (8个)
roll_initiative - 先攻投骰
roll_attack - 攻击检定
roll_dmg - 伤害投骰
roll_spell_attack - 法术攻击
roll_save - 豁免检定
roll_skill_check - 技能检定
opportunity_attack - 借机攻击… See the full description on the dataset page: https://huggingface.co/datasets/autoprogrammer/dnd-training-sharegpt-dm.sharegpt-regen-qwen3-8b-non-thinking
ShareGPT Regen Qwen3-8B Non-Thinking 40K Clean
中文
本仓库包含 ShareGPT 数据经 Qwen3-8B non-thinking 模式重新生成、长输出重试和退化样本清理后的版本。原始 4K regen 的 max-token 命中样本依次经过 16K、40K retry；最终移除了 context length 超限、尾部退化/重复、以及人工确认的无界生成样本。
文件
文件
说明
行数
data/train-00000-of-00004.parquet
Hugging Face parquet 分片
10,944
data/train-00001-of-00004.parquet
Hugging Face parquet 分片
10,944
data/train-00002-of-00004.parquet
Hugging Face parquet 分片
10,943… See the full description on the dataset page: https://huggingface.co/datasets/heiheiha798/sharegpt-regen-qwen3-8b-non-thinking.sharegpt_cot_dataset
A data set inspired by the "Reflection" method, three-dimensional thinking and cot
This is the ShareGPT format.
The data set was generated using multiple llm synthesis.
shisa-v2-sharegpt
shisa-v2-sharegpt
This is an updated version of the original shisa-v1 dataset augmxnt/ultra-orca-boros-en-ja-v1 and retains the same conversations field and sharegpt formatting to facilitate its use as drop-in replacement for the original dataset.
The shisa-v2 revision filters a few entries, but largely retains the exact composition and prompts of the original.
All responses have been entirely regenerated from open weight models (Athene V2, Llama 3.3 70B, and Tulu 3 405B)
Outputs… See the full description on the dataset page: https://huggingface.co/datasets/shisa-ai/shisa-v2-sharegpt.orca-agentinstruct-1M-v1-cleaned-fixed-sharegpt
Orca Agentic Instruct - ShareGPT
Entries with empty assistant turn were removed
messages were converted into ShareGPT
Initial number of examples: 1046410
Number of examples removed: 68
Remaining examples: 1046342
Removal rate: 0.01%
Credit
mlabonne/orca-agentinstruct-1M-v1-cleaned
ShareGPT-Qwen3-4B-T0.6-Thinking-Regen
ShareGPT — Qwen3-4B Thinking Regeneration (T0.6, 32k budget)
This dataset contains 36,315 ShareGPT conversations with assistant responses regenerated by Qwen/Qwen3-4B in thinking mode. User prompts are retained; each regenerated assistant turn includes its reasoning in reasoning_content and its final answer in content.
The prompt set (system and user messages, including the "You are a helpful assistant." system turn) is exactly the one of… See the full description on the dataset page: https://huggingface.co/datasets/jgeuter/ShareGPT-Qwen3-4B-T0.6-Thinking-Regen.Reddit-SFW-Writing_Prompts_ShareGPT_Curated
Normalized SFW Reddit Writing Prompts
Dataset Description
This dataset is a normalized, flattened version of curated Reddit writing prompts, specifically derived from ChaoticNeutrals/Reddit-SFW-Writing_Prompts_ShareGPT. It maps nested conversational arrays into a strict instruction-response schema, making it highly optimized for instruction-tuning Large Language Models.
Dataset Schema
Column Name
Type
Description
prompt
string
The input prompt, user… See the full description on the dataset page: https://huggingface.co/datasets/rafy2342/Reddit-SFW-Writing_Prompts_ShareGPT_Curated.kurumi-sharegpt-cn
时崎狂三 角色扮演对话数据集
《约会大作战》角色「时崎狂三」的纯中文多轮对话数据集，用于微调角色扮演 LLM。
统计
样本数：1188 条
轮次：每条 4 轮（human → gpt → human → gpt）
语言：纯中文（无日文假名），保留中文口癖「啊啦啊啦 / 呵呵 / 贵安」
覆盖：日常起居、情感亲密、休闲爱好、节日时刻、角色设定问答、情绪表达、动作描写等约 200 类场景
格式（ShareGPT）
{
"system": "你是时崎狂三，……（人设卡）",
"conversations": [
{"from": "human", "value": "主人说的话"},
{"from": "gpt", "value": "狂三的回复"},
{"from": "human", "value": "……"},
{"from": "gpt", "value": "……"}
]
}
使用（LLaMA-Factory）… See the full description on the dataset page: https://huggingface.co/datasets/justinQAQ/kurumi-sharegpt-cn.humor-sharegpt-5k
Humor ShareGPT 5K
A curated dataset of 5,234 jokes, riddles, puns, and humor in ShareGPT conversational format, designed for fine-tuning small language models.
Format
Each example is a multi-turn conversation in ShareGPT format with a category label:
{
"conversations": [
{"from": "human", "value": "Tell me a dad joke"},
{"from": "gpt", "value": "Why don't eggs tell jokes? They'd crack each other up!"}
],
"category": "dad_joke"
}
Multi-turn examples… See the full description on the dataset page: https://huggingface.co/datasets/briancconnelly/humor-sharegpt-5k.