datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Multi-turn_Long-context_Benchmark_for_LLMs
LoopServe: An Adaptive Dual-phase LLM Inference Acceleration System for Multi-Turn Dialogues
Arxiv: https://www.arxiv.org/abs/2507.13681
Huggingface: https://huggingface.co/papers/2507.13681
Introduction
LoopServe Multi-Turn Dialogue Benchmark is a comprehensive evaluation dataset comprising multiple diverse datasets designed to assess large language model performance in realistic conversational scenarios.
Unlike traditional benchmarks that place queries only at the end… See the full description on the dataset page: https://huggingface.co/datasets/TreeAILab/Multi-turn_Long-context_Benchmark_for_LLMs.multiturn-chatAll-CVE-Chat-MultiTurn-1999-2025-Dataset
CVE Chat‑Style Multi‑Turn Cybersecurity Dataset (1999 – 2025)
1. Project Overview
This repository hosts the largest publicly available chat‑style, multi‑turn cybersecurity dataset to date, containing ≈ 300 000 Common Vulnerabilities and Exposures (CVE) records published between 1999 and 2025. Each record has been meticulously parsed, enriched, and converted into a conversational format that is ideal for training and evaluating AI and AI‑Agent systems focused on… See the full description on the dataset page: https://huggingface.co/datasets/Trendyol/All-CVE-Chat-MultiTurn-1999-2025-Dataset.Multi-Turn-Conversational-SFTCreated by: DataCreator AI
Multi-Domain Multi-Turn Chat Conversations Dataset
A synthetic conversational dataset designed for LLM supervised fine-tuning and chatbot training.
The dataset contains multi-turn dialogues across multiple everyday domains such as travel, banking, health, programming, and customer interactions. Conversations are structured in OpenAI chat fine-tuning format, making the dataset directly usable in modern fine-tuning pipelines.
Dataset Overview… See the full description on the dataset page: https://huggingface.co/datasets/DataCreatorAI/Multi-Turn-Conversational-SFT.multi-turn-chat-sft-50k
Multi-Turn Chat SFT (50K ShareGPT Format)
50,000 multi-turn conversations in ShareGPT format for supervised fine-tuning of chat models.
Format
Standard ShareGPT format — drop-in compatible with LLaMA-Factory, Axolotl, and Unsloth:
{
"conversations": [
{"from": "system", "value": "You are a helpful assistant."},
{"from": "human", "value": "Write a Python function to implement binary search."},
{"from": "gpt", "value": "Here's a clean… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/multi-turn-chat-sft-50k.MultiTurn-Chat-MT-Bench
SEA-MTBench
SEA-MTBench evaluates a model's ability to engage in multi-turn (2 turns) conversations and respond in ways that align with human needs. We use gpt-4-1106-preview as the judge model and compare against gpt-3.5-turbo-0125 as the baseline model. It is based on MT-Bench and was manually translated by native speakers for Indonesian (id), Javanese (jv), Sundanese (su), and Vietnamese (vi). The Thai split of this dataset uses MT-Bench Thai from the ThaiLLM leaderboard.… See the full description on the dataset page: https://huggingface.co/datasets/aisingapore/MultiTurn-Chat-MT-Bench.multiturn-feedback
MultiTurn Feedback Dataset
Multi-turn conversation feedback dataset with sparse and dense annotations.
Dataset Description
This dataset contains human feedback annotations for paper "User Feedback in Human-LLM Dialogues:
A Lens to Understand Users But Noisy as a Learning Signal". It includes two evaluation subsets:
Sparse: 75 conversations from LMSYS-Chat-1M with sparse feedback
Dense: 74 conversations from LMSYS-Chat-1M + 34 WildChat with dense feedback
Labels… See the full description on the dataset page: https://huggingface.co/datasets/yuhan-nlp/multiturn-feedback.glm-4.7-multiturn-CoT
glm-4.7-multiturn-CoT
Dataset Summary
glm-4.7-multiturn-CoT is a ShareGPT-style multi-turn reasoning distillation dataset generated with GLM-4.7 as the teacher model.
This release focuses on preserving multi-turn dialogue continuity while injecting explicit chain-of-thought style responses in assistant turns.
Key Features
Multi-turn conversation format (human / gpt)
Assistant responses stored as <think>...</think> + final answer
Resume-safe distillation… See the full description on the dataset page: https://huggingface.co/datasets/Jackrong/glm-4.7-multiturn-CoT.kuza_sft_multiturn
Kuza SFT Multi-turn
Supervised fine-tuning data for Kuza, an offline agricultural assistant
for smallholder farmers and agricultural extension workers in East Africa
(English and Swahili). This repository is one of four Kuza SFT datasets.
Dataset description
Hand-authored four-turn English and Swahili dialogs. The first assistant turn asks a clarifying question (crop, location, symptom); the second gives concrete farm advice and avoids invented pesticide or… See the full description on the dataset page: https://huggingface.co/datasets/kuzaai/kuza_sft_multiturn.curatorkit-testrun-Multiturn
curatorkit-testrun-Multiturn
Built using CuratorKIT — provenance-grounded curation and synthesis for LLM post-training.
Method
multiturn
Backend
litellm
Model
openai/Qwen/Qwen2.5-0.5B-Instruct
Formats
alpaca, sharegpt
Artifact
dataset
Published
2026-08-28 10:04 UTC
Usage
from datasets import load_dataset
ds = load_dataset("ram-lexsi/curatorkit-testrun-Multiturn", "alpaca")
all-cve-chat-multiturn-1999-2025
CVE Chat‑Style Multi‑Turn Cybersecurity Dataset (1999 – 2025)
1. Project Overview
This repository hosts the largest publicly available chat‑style, multi‑turn cybersecurity dataset to date, containing ≈ 300 000 Common Vulnerabilities and Exposures (CVE) records published between 1999 and 2025. Each record has been meticulously parsed, enriched, and converted into a conversational format that is ideal for training and evaluating AI and AI‑Agent systems focused on… See the full description on the dataset page: https://huggingface.co/datasets/ansulev/all-cve-chat-multiturn-1999-2025.chatalpaca-multiturn-enriched-2
chatalpaca-multiturn-enriched-2
Records in data.jsonl: 7924
Source dataset: BRlkl/chatalpaca-multiturn-enriched
Generated with scenario-guided Samantha multiturn revision
aka-llama-korean-dataset-multiturn-raw
Aka-LLAMA Korean Multi-Turn Dataset (Raw)
This dataset is a raw version of a multi-turn Korean conversation dataset generated using kordinal. It is designed for research and development in Korean natural language processing (NLP), specifically in multi-turn dialogue generation.
License
This dataset is released under the CC BY-NC 4.0 license. It is strictly for non-commercial research and educational purposes. Commercial usage is prohibited.
Additionally, some data… See the full description on the dataset page: https://huggingface.co/datasets/snupilab/aka-llama-korean-dataset-multiturn-raw.multiturn_chat_0.8m-chinese-zhtw
Dataset Card for "multiturn_chat_0.8m-chinese-zhtw"
內容
包含約 80 萬條由 BELLE 專案所產生的 Human 與 Assistant 的多輪對話。
注意：此資料集是由 ChatGPT 產生的，未經嚴格校驗，內容可能包含錯誤。使用過程中請注意這一點。
instruction 中包含多輪對話的上文內容，以 Human: 和 Assistant: 區分，output 中包含當前 Assistant 角色的回答。
範例
{
"instruction": "Human:請根據題材「健身房」，寫一篇800字的文章。 \nAssistant:好的，以下是由我生成的800字「健身房」主題文章：\n在現代社會，人們越來越珍惜健康和身材。健身房就是一個人們可以鍛鍊身體的場所，也是一個社交的場所。在健身房，人們可以透過器材訓練，有氧運動和瑜珈等方式來達到健身的目的。… See the full description on the dataset page: https://huggingface.co/datasets/erhwenkuo/multiturn_chat_0.8m-chinese-zhtw.Synthetic_UAV_Scenario_LLM_MultiTurn_GPS_Navigation
Dataset Card for CJJones/Synthetic_UAV_Scenario_LLM_MultiTurn_GPS_Navigation
The full CJ Jones' synthetic dataset catalog is available at: https://datadeveloper1.gumroad.com
Want more? 🚀 Get the AI Startup Bundle from Gumroad.
Dataset Summary
This dataset contains synthetic multi-turn UAV (Unmanned Aerial Vehicle) flight scenarios with realistic GPS navigation challenges, flight mode transitions, and system diagnostics. The scenarios simulate various flight conditions… See the full description on the dataset page: https://huggingface.co/datasets/CJJones/Synthetic_UAV_Scenario_LLM_MultiTurn_GPS_Navigation.gsm8k_multiturnThe "socratic" version of GSM8K has the model reflect and ask itself sub-questions about the initial question, before coming to a final answer.
This dataset reformats the socratic GSM8K version into a multi-turn conversation, where the sub-questions are asked by the user rather than being self-asked by the model.
fama_fraternitatis_multiturn
Fama Fraternitatis Rosae Crucis Multiturn Conversation Dataset
Overview
This dataset consists of structured multiturn conversations modeled around the esoteric and philosophical themes of the "Fama Fraternitatis." The text, known for its deep allegorical content, serves as the foundation for generating dialogues that involve rigorous inquiry into the occult and philosophical.
Objective
The primary objective of this dataset is to facilitate the development and… See the full description on the dataset page: https://huggingface.co/datasets/alexandreteles/fama_fraternitatis_multiturn.kernelbook-opus4.8-multiturn-traces
KernelBook → Triton: Multi-Turn Generation Traces (Opus 4.8)
Multi-turn agentic traces of Claude Opus 4.8 converting PyTorch modules into
Triton GPU kernels. Each row is one problem from
GPUMODE/KernelBook: the model
writes a kernel, runs it on a GPU against the reference, reads the
correctness + speedup feedback, and iterates — so every trace is a grounded,
tool-using optimization loop, not a single-shot completion.
How it was generated
Model: claude-opus-4-8… See the full description on the dataset page: https://huggingface.co/datasets/ppbhatt500/kernelbook-opus4.8-multiturn-traces.kernelbook-triton-multiturn-reasoning-traces
KernelBench Triton Multi-Turn Reasoning Traces
A dataset of multi-turn reasoning traces for Triton GPU kernel generation from PyTorch reference implementations. Each trace captures the full iterative refinement loop — model reasoning, generated kernel code, execution feedback, and benchmark results.
Generation Setup
Model & Serving
Problems were sent to Qwen3-235B-A22B-Thinking-2507 (FP8) served via vLLM on H100 GPUs (tensor parallel, 131k context window). Reasoning… See the full description on the dataset page: https://huggingface.co/datasets/ppbhatt500/kernelbook-triton-multiturn-reasoning-traces.DiscoverLLM-multiturn-preferences
DiscoverLLM: Multi-turn Preference Dataset
Multi-turn dialogue data with scored candidate completions, produced by best-of-N
synthesis over the DiscoverLLM user simulator
(paper · project page).
Each example is a single turn of a simulated user–assistant conversation with one of
several candidate assistant responses and an associated reward score, intended for
offline DPO / GRPO / reward-model training.
Configs
Config
Rows
Task
creative_writing
3,052… See the full description on the dataset page: https://huggingface.co/datasets/kixlab/DiscoverLLM-multiturn-preferences.appellatio_fraternitatis_rosae_crucis_multiturn
Appellatio Fraternitatis Rosae Crucis Multiturn Conversation Dataset
Overview
This dataset consists of structured multiturn conversations modeled around the esoteric and philosophical themes of the "Appellatio Fraternitatis Rosae Crucis." The text serves as the foundation for generating dialogues that involve rigorous inquiry into the occult and philosophical.
Objective
The primary objective of this dataset is to facilitate the development and testing of AI… See the full description on the dataset page: https://huggingface.co/datasets/alexandreteles/appellatio_fraternitatis_rosae_crucis_multiturn.Gardening_LLM_Synthetic_Training_Multiturn_DialogWant more? 🚀 Get the AI Startup Bundle from Gumroad.
Gardening LLM Synthetic Training - Multiturn Dialog Dataset
Dataset Description
This dataset contains a sample of synthetic multiturn conversations between home gardeners and an expert gardening assistant ("GardenBot"). The conversations cover five key gardening topics with detailed subtopics and plant-specific advice, designed for training conversational LLMs.
Dataset Overview
Curated by: CJ Jones… See the full description on the dataset page: https://huggingface.co/datasets/CJJones/Gardening_LLM_Synthetic_Training_Multiturn_Dialog.chatalpaca-multiturn-enriched-3.5
chatalpaca-multiturn-enriched-3.5
This dataset combines the existing Samantha A10 multiturn corpus with new long-memory and exact-answer specialist conversations.
Splits
train: 18,801 rows (existing, manual-evaluation, and generated rows)
No separate validation split is published; all records remain in train.
Total: 18,801 rows
Composition
Existing source artifact: BRlkl/chatalpaca-multiturn-enriched-2.1
New long-memory rows: 8,000
New arithmetic… See the full description on the dataset page: https://huggingface.co/datasets/BRlkl/chatalpaca-multiturn-enriched-3.5.nepali_alpaca_multiturn
ShareGPT Conversations
This repository contains multi-turn human ↔ gpt conversations.
Splits
dineshkarki/nepali_alpaca_multiturn provides a split named train by default.
Usage
from datasets import load_dataset
ds = load_dataset("dineshkarki/nepali_alpaca_multiturn")
train = ds["train"]
Schema
Each row contains:
id: unique string
conversations: list of N messages (N ≥ 2), alternating human and gpt roles
Notes:
Conversations are lightly… See the full description on the dataset page: https://huggingface.co/datasets/dineshkarki/nepali_alpaca_multiturn.tiny-multiturn-chat-kochymical_wedding_of_christian_rosenkreutz_multiturn
The Chymical Wedding of Christian Rosenkreutz Multiturn Conversation Dataset
Overview
This dataset consists of structured multiturn conversations modeled around the esoteric and philosophical themes of "The Chymical Wedding of Christian Rosenkreutz." The text, known for its deep allegorical content, serves as the foundation for generating dialogues that involve rigorous inquiry into the occult and philosophical.
Objective
The primary objective of this dataset… See the full description on the dataset page: https://huggingface.co/datasets/alexandreteles/chymical_wedding_of_christian_rosenkreutz_multiturn.multi-turn_dataset
Multi-turn Prompts Dataset
Description
This dataset consists of 400 text-only fine-tuned versions of multi-turn conversations in the English language based on 10 categories and 19 use cases. It has been generated with ethically sourced human-in-the-loop data methods and aligned with supervised fine-tuning, direct preference optimization, and reinforcement learning through human feedback.
The human-annotated data is focused on data quality and precision to enhance the… See the full description on the dataset page: https://huggingface.co/datasets/SoftAge-AI/multi-turn_dataset.multiturn-legal-argumentation
Dataset Card for Multi-Turn Legal Argumentation
Dataset Description
Multi-Turn Legal Argumentation is a legal reasoning dataset designed for supervised fine-tuning of language models acting as judges in a moot court simulator.
Each example represents a turn in a courtroom-style argumentation process, where a judge evaluates arguments presented by either the petitioner or respondent and produces structured feedback, score updates, courtroom responses, and internal… See the full description on the dataset page: https://huggingface.co/datasets/snowsadh/multiturn-legal-argumentation.chatalpaca-multiturn-enriched-probe
ChatAlpaca Multiturn Enriched Probe
Deterministic transcript-memory probe dataset for Samantha multiturn latent-state pretraining.
Source dataset: BRlkl/chatalpaca-multiturn-enriched
Each conversation keeps the original messages and adds state_supervision with one fixed probe for every prefix after the first user/assistant pair.
Fixed probe question:
What is everything we have talked about so far? Give exact conversation transcript verbatim in following format: [User 1]: X… See the full description on the dataset page: https://huggingface.co/datasets/BRlkl/chatalpaca-multiturn-enriched-probe.multiturn_chat_milei_gpt
Milei-GPT Dataset
Che y si queremos hacer un LLM que hable de la misma forma que un famoso ... como hacemos? Este repo es una excusa para aprender a preparar un dataset para fine-tunear algún LLM, aprender como evaluarlo, como tokenizarlo, como extenderlo de formar sintética, y tantas otras cosas. Al final, si todo sale bien, vamos a tener un modelo que va a hablar como la persona que elegimos, y le podemos poner un RAG (retrieval augmented generation) encima para que nos traiga un… See the full description on the dataset page: https://huggingface.co/datasets/machinelearnear/multiturn_chat_milei_gpt.