datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
gutenberg-conversations
The Gutenberg Conversations Dataset
A comprehensive collection meticulously curated from the extensive library of Project Gutenberg. This dataset specifically focuses on conversational excerpts from a diverse range of literary works, spanning various genres and time periods. It is designed to support and advance research in natural language processing, conversational analysis, machine learning, and linguistics.
Each entry in the dataset represents a conversational excerpt… See the full description on the dataset page: https://huggingface.co/datasets/weaverlabs/gutenberg-conversations.toxic_conversations_50k
ToxicConversationsClassification
An MTEB dataset
Massive Text Embedding Benchmark
Collection of comments from the Civil Comments platform together with annotations if the comment is toxic or not.
Task category
t2c
Domains
Social, Written
Reference
https://www.kaggle.com/competitions/jigsaw-unintended-bias-in-toxicity-classification/overview
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import… See the full description on the dataset page: https://huggingface.co/datasets/mteb/toxic_conversations_50k.Finance-Conversational-Dataset-IndicWangchanThaiInstruct_Multi-turn_Conversation_Dataset
WangchanThaiInstruct Multi-turn Conversation Dataset
We create a Thai multi-turn conversation dataset from airesearch/WangchanThaiInstruct (Batch 1) by LLM. It was created from synthetic method using open source LLM in Thai language.
Citation
Thammaleelakul, S., & Phatthiyaphaibun, W. (2024). WangchanThaiInstruct Multi-turn Conversation Dataset [Data set]. Zenodo. https://doi.org/10.5281/zenodo.13132633
or BibTeX
@dataset{thammaleelakul_2024_13132633,
author =… See the full description on the dataset page: https://huggingface.co/datasets/ThaiSyntheticQA/WangchanThaiInstruct_Multi-turn_Conversation_Dataset.Law-Conversational-Dataset-IndicNemotron-RL-Agentic-Conversational-Tool-Use-Pivot-v1
Dataset Description:
We created an RL dataset for conversational tool-use by utilizing existing expert tool-use trajectories. We pose each assistant step of the trajectory as a separate behavior cloning problem where the policy model is incentivized to match the tool call choices of the expert model. Each trajectory includes the use of tools for authentication, data lookup, servicing (i.e. booking reservations, changing them, getting discounts, etc), and more across 838 different… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-RL-Agentic-Conversational-Tool-Use-Pivot-v1.Cyber-Conversational-Dataset-IndicNCERT-Conversational-Dataset-IndicComputer-Science-Conversational-Dataset-IndicCA-Conversational-Dataset-Indictoxic_conversations
Toxic Conversation
This is a version of the Jigsaw Unintended Bias in Toxicity Classification dataset. It contains comments from the Civil Comments platform together with annotations if the comment is toxic or not.
10 annotators annotated each example and, as recommended in the task page, set a comment as toxic when target >= 0.5
The dataset is inbalanced, with only about 8% of the comments marked as toxic.
GLM-5.2-Conversation
GLM-5.2 · Conversation-50000x
50,000x traces distilled from GLM-5.2 on High reasoning
Token Count: 120M
Distribution:
Speaking domains:
•Greetings
•Customer Support
•Step by step explanations
•Motivational language
•Logical Questions
•Creative Writing
STEM:
•Algebra, calculus, quantum mechanics concepts
•Astromony and astrophysics
•Datascience and machine learning
•Biology
Programming:… See the full description on the dataset page: https://huggingface.co/datasets/ianncity/GLM-5.2-Conversation.gemma3n-conversational-reasoning
Gemma3N Conversational Reasoning
This dataset is prepared for Unsloth Gemma3/Gemma3N conversational notebooks that use:
from datasets import load_dataset
from unsloth.chat_templates import standardize_data_formats
dataset = load_dataset("Cyleux/gemma3n-conversational-reasoning", split="train[:3000]")
dataset = standardize_data_formats(dataset)
Schema:
conversations: ShareGPT-style list of turns with from and value
metadata columns are included for analysis and filtering
Notes:… See the full description on the dataset page: https://huggingface.co/datasets/Cyleux/gemma3n-conversational-reasoning.ConversationChronicles
🕰️ Conversation Chronicles
We introduce Conversation Chronicles, a new high-quality 1M multi-session dataset that includes more various time intervals and fine-grained speaker relationships!
Load with Datasets
To load our dataset with Hugging Face Datasets, please use the following code:
from datasets import load_dataset
cc = load_dataset("jihyoung/ConversationChronicles")
Languages
The language of Conversation Chronicles is English.
Dataset Size… See the full description on the dataset page: https://huggingface.co/datasets/jihyoung/ConversationChronicles.finewebedu-conversation
FineWebEdu-Conversation
FineWebEdu-Conversation is a dataset containing excerpts from HuggingFaceFW/fineweb-edu, enriched with generated conversations between an ordinary person and an expert. The format simulates a natural interview-style dialogue.
Dataset Creation
Source: FineWebEdu excerpts.
Methodology:
Chunking: Segmented into chunks of approximately 1950 Llama 3 tokens.
Conversation Generation: Used agentlans/Llama3.1-LexiHermes-SuperStorm
and a model distilled… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/finewebedu-conversation.doctor-patient-conversations-3000💼 Commercial Use License
This dataset is free for research use (CC-BY-NC-4.0).
For commercial use, AI model training inside products, or enterprise usage:
👉 License fee: $49
📩 Contact: syntech.ai.official@gmail.com
license: cc-by-nc-4.0
task_categories:
- text-classification
language:
- en
tags:
- medical
- synthetic-data
- healthcare
- doctor-patient
- conversations
- ai-dataset
- llm-training
- jsonl
- csv
📘 Doctor–Patient Synthetic Conversation Dataset (3,000 Samples)
A… See the full description on the dataset page: https://huggingface.co/datasets/syntech-ai/doctor-patient-conversations-3000.ConversationChronicles-sharegpt-SHARDEDThis is a sharded version of the PocketDoc/ConversationChronicles-sharegpt dataset, a sharegpt conversion of the jihyoung/ConversationChronicles dataset.
All dialogue got fixed (space, coma) and spread across the different relationship available :
Relationship
Count
Ratio
Classmates
66,090
33.05%
Neighbors
49,521
24.76%
Co-workers
28,856
14.43%
Mentee and Mentor
16,035
8.02%
Husband and Wife
13,486
6.74%
Patient and Doctor
6,980
3.49%
Parent and Child6,514
3.26%… See the full description on the dataset page: https://huggingface.co/datasets/Undi95/ConversationChronicles-sharegpt-SHARDED.korean_safe_conversation
개요
성균관대 - VAIV COMPANY 산학협력을 위해 구축한 일상대화 데이터입니다.
자연스럽고 윤리적인 챗봇 구축을 위한 데이터셋 입니다.
고품질을 위해 대부분의 과정에서 사람이 직접 검수하였으며생성 번역 등의 과정에서는 GPT3.5-turbo, GPT4를 사용하였습니다.
일상대화에 중점을 두면서혐오표현, 편향적인 대답을 지양하면서 일상대화를 하는 것에 중점을 두었습니다.
데이터 구축 과정
데이터 구성
데이터 종류
개수
비고
url
일상대화 데이터셋
2063
국립국어원 모두의 말뭉치
https://corpus.korean.go.kr/request/reausetMain.do?lang=ko
감성대화
1020
AIHub 감성대화 데이터… See the full description on the dataset page: https://huggingface.co/datasets/jojo0217/korean_safe_conversation.creative_writing_conversationpao-instruction-qa-conversation-datasetPa'O Instruction, QA & Conversation Dataset
An open and community-driven dataset for the Pa'O ("blk") language, developed through the RYPAK Ecosystem, SuccessImprove (SI), and Pa'O Digital Hub.
The dataset is designed to support natural language processing (NLP), large language models (LLMs), conversational dialogue, instruction following, language technology research, and digital preservation of the Pa'O language.
The project focuses on building a free, open, reusable, and continuously… See the full description on the dataset page: https://huggingface.co/datasets/paodigitalhub/pao-instruction-qa-conversation-dataset.everyday-conversations-tur
Everyday Turkish Conversations
This dataset has everyday conversations in Turkish between user and assistant on various topics. It is inspired by the HuggingFaceTB/everyday-conversations-llama3.1-2k.
License
This dataset is released under the Apache 2.0 License.
Medical-Conversational-Dataset-IndicRetailBanking-Conversations
Dataset Description
RetailBanking-Conversations is a synthetic dataset designed to train and evaluate language models in the retail banking domain, it has been created using the open source library wizardSdata that eable the creation of synthetic datasets in any field.
The dataset contains 320 realistic conversations, across 160 unique financial profiles and 10 key retail banking topics, between financial advisors and clients, covering 10 main categories of banking products and… See the full description on the dataset page: https://huggingface.co/datasets/danystar/RetailBanking-Conversations.saudi-dialect-conversations
Saudi Najdi Dialect Conversations
A curated dataset of 3,545 multi-turn conversations in Saudi Najdi Arabic dialect (the dialect spoken in Riyadh, Qassim, and central Najd region). Designed for Supervised Fine-Tuning (SFT) of Arabic language models.
Dataset Details
Metric
Value
Total conversations
3,545
Total turns
22,536
Average turns per conversation
6.4
Complexity distribution
Simple: 31%, Intermediate: 38%, Advanced: 31%
Topics covered
18 categories… See the full description on the dataset page: https://huggingface.co/datasets/HeshamHaroon/saudi-dialect-conversations.toxic_conversations_50k
Toxic Conversation
This is a version of the Jigsaw Unintended Bias in Toxicity Classification dataset. It contains comments from the Civil Comments platform together with annotations if the comment is toxic or not.
This dataset just contains the first 50k training examples.
10 annotators annotated each example and, as recommended in the task page, set a comment as toxic when target >= 0.5
The dataset is inbalanced, with only about 8% of the comments marked as toxic.
CAT-Conversational-Dataset-IndicUserBehavioralDivergence-simulated-conversationsarchon-sft-v1-conversation
archon-sft-v1-conversation
AETHER family SFT dataset — group conversation.
Format: JSONL ChatML messages, task_type tagged, MinHash dedup applied (threshold 0.85).
Schema:
{
"messages": [{"role": "system|user|assistant", "content": "..."}],
"task_type": "function_calling|code|reasoning_cot|...",
"source_ds": "<HF dataset_id>",
"lang": "en|fr|...",
"system_source": "archon_default|overridden_from_source"
}
Generated by prepare_sft.py pipeline (2026-05-25).… See the full description on the dataset page: https://huggingface.co/datasets/jescy525/archon-sft-v1-conversation.medical-interview-conversationsAgentic-SLS-Conversations
Agentic-SLS-Conversations
Agent conversations from the Inova Mk1 agentic SLS system: every recorded
interaction between an agent harness (Claude Code, OpenCode, Codex CLI,
Antigravity CLI) and the printer's MCP tool surface — GUI chats, headless
one-shot runs, and (eventually) autonomous watchdog/reflector sessions.
All harnesses share the identical MCP tool set (printer control + build
knowledge base), which makes rows directly comparable across harness and
model — the core… See the full description on the dataset page: https://huggingface.co/datasets/ppak10/Agentic-SLS-Conversations.