datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
apptek_callcenter_dialogues
AppTek Call-Center Dialogues: A Multi-Accent Long-Form Benchmark for English ASR
AppTek Call-Center Dialogues is a long-form conversational speech dataset for automatic speech recognition (ASR), featuring diverse English accents
across multiple service-oriented domains and designed to evaluate models on realistic call-center interactions.
128.6 hours of speech
14 English accent groups
16 service domains
5–15 minute conversations (long-form)
Split-channel audio (one… See the full description on the dataset page: https://huggingface.co/datasets/apptek-com/apptek_callcenter_dialogues.empathetic_dialogues_for_lmrussian_dialoguesДатасет русских диалогов собранных с Telegram чатов.
Диалоги имеют разметку по релевантности.
Также были сгенерированы негативные примеры с помощью перемешивания похожих ответов.
Количество диалогов - 2 миллиона
Формат датасета:
{
'question': 'Привет',
'answer': 'Привет, как дела?'
'relevance': 1
}
Программа парсинга: https://github.com/Den4ikAI/telegram_chat_parser
Citation:
@MISC{russian_instructions,
author = {Denis Petrov},
title = {Russian dialogues… See the full description on the dataset page: https://huggingface.co/datasets/Den4ikAI/russian_dialogues.Discord-Dialogues
Discord-Dialogues is a large-scale dataset of anonymized Discord conversations from late spring to early fall 2025 for training and evaluating realistic conversational AI models in a ChatML-friendly format.
This dataset contains 7.3 million exchanges spread out over 16 million turns, with more than 139 million words.
Nomic Atlas Map
Features
Mixed single and multi-turn exchanges
Human-only dialogues (no bots)
Filtered for ToS and harmful contentLinks… See the full description on the dataset page: https://huggingface.co/datasets/mookiezi/Discord-Dialogues.russian_dialogues_2
Den4ikAI/russian_dialogues_2
Датасет русских диалогов для обучения диалоговых моделей.
Количество диалогов - 1.6 миллиона
Формат датасета:
{
'sample': ['Привет', 'Привет', 'Как дела?']
}
Citation:
@MISC{russian_instructions,
author = {Denis Petrov},
title = {Russian context dialogues dataset for conversational agents},
url = {https://huggingface.co/datasets/Den4ikAI/russian_dialogues_2},
year = 2023
}
turkish-daily-dialogues-5k
Turkish Daily Dialogues 5K
Exactly 5,000 synthetic, multi-turn Turkish conversations covering ordinary daily-life situations. The corpus is designed as a small, auditable baseline for dialogue modelling, instruction-format experiments, augmentation research, and Turkish-language evaluation—not as a substitute for conversations written by real people.
Provenance in one sentence: the Turkish source scenario library was drafted with AI assistance specifically for this project… See the full description on the dataset page: https://huggingface.co/datasets/3nesdeniz/turkish-daily-dialogues-5k.Question-Anchored-Tutoring-Dialogues-2k
Question-Anchored-Tutoring-Dialogues-2k
This dataset contains dialogues from math tutoring interventions recorded on Eedi.
Dataset Details
Dataset Description
Each dialogue represents a chat-based conversation between a tutor and a student prompted by the student requesting assistance while working on a lesson. Dialogues are accompanied with 2 sources of meta-data:
DQ-Question-Metadata: The question the student was working on that prompted the tutoring… See the full description on the dataset page: https://huggingface.co/datasets/Eedi/Question-Anchored-Tutoring-Dialogues-2k.paralinguistic_dialoguesknowchat-multi-turn-dialogues
KnowChat: Multi-Turn Human-LLM Dialogues on Knowledge Tasks
KnowChat is a dataset of 705 multi-turn human-LLM conversations collected to validate the KnowSim user simulation framework. It pairs each conversation with pre/post knowledge assessments, self-reported survey ratings, and participant background information, enabling research on information calibration -- how well LLM assistants tailor responses to users with different knowledge levels.
Dataset Summary… See the full description on the dataset page: https://huggingface.co/datasets/yjlee36/knowchat-multi-turn-dialogues.soccer-dialoguesrussian_dialogues_2_parquet
russian_dialogues_2 (Parquet mirror)
A Parquet mirror of Den4ikAI/russian_dialogues_2,
converted from dataset.jsonl.gz into Parquet shards (~12MB each) for native streaming and sharding.
empathetic_dialogues_llm
Empathetic Dialogues for LLM
This repository contains a reformatted version of the Empathetic Dialogues dataset, tailored for seamless integration with Language Model (LLM) training and inference. The original dataset's format posed challenges for direct application in LLM tasks, prompting us to restructure and clean the data.
Data Restructuring
We have implemented the following changes to enhance the dataset's usability:
Merged dialogues with the same conv_id… See the full description on the dataset page: https://huggingface.co/datasets/Estwld/empathetic_dialogues_llm.empathetic-dialogues-contexts
Dataset Description
This is a dataset of emotional contexts that was retrieved from the original EmpatheticDialogues (ED) dataset. Respondents were asked to describe an event that was associated with a particular emotion label (i.e. p(event|emotion).
There are 32 emotion labels in total.
There are 19209, 2756, and 2542 instances of emotional descriptions in the train, valid, and test set, respectively.
danish-tool-dialogues-v9
danish-tool-dialogues-v1
Danish multi-turn tool-use conversations with reasoning, translated from the
Glaive subset of
Nanbeige/ToolMind
(Apache-2.0) by scripts/translate_toolmind_da.py.
Complements danish-tool-calls-v1, which is single-turn and synthetic. Here
the conversations run several turns, tool results are fed back, and the
assistant reasons before calling.
split
rows
train
34,168
eval_seen_tools
698
eval_unseen_tools
768
eval_seen_sym
752… See the full description on the dataset page: https://huggingface.co/datasets/jensjepsen/danish-tool-dialogues-v9.know_medical_dialogues
🩺 Description:
The knowrohit07/know_medical_dialogues dataset is a collection of conversational exchanges between patients and doctors on various medical topics. It aims to capture the intricacies, uncertainties, and questions posed by individuals regarding their health and the medical guidance provided in response.
🎯 Intended Use:
This dataset is crafted for training Large Language Models (LLMs) with a focus on understanding and generating medically-informed dialogue.… See the full description on the dataset page: https://huggingface.co/datasets/knowrohit07/know_medical_dialogues.sdsd-dialogues
Self Directed Synthetic Dialogues (SDSD) v0
This dataset is an experiment in procedurally generating synthetic dialogues between two language models.
For each dialogue, one model, acting as a "user" generates a plan based on a topic, subtopic, and goal for a conversation.
Next, this model attempts to act on this plan and generating synthetic data.
Along with the plan is a principle which the model, in some successful cases, tries to cause the model to violate the principle resulting… See the full description on the dataset page: https://huggingface.co/datasets/allenai/sdsd-dialogues.danish-tool-dialogues-v6
danish-tool-dialogues-v1
Danish multi-turn tool-use conversations with reasoning, translated from the
Glaive subset of
Nanbeige/ToolMind
(Apache-2.0) by scripts/translate_toolmind_da.py.
Complements danish-tool-calls-v1, which is single-turn and synthetic. Here
the conversations run several turns, tool results are fed back, and the
assistant reasons before calling.
split
rows
train
17,667
eval_seen_tools
722
eval_unseen_tools
779
933 distinct tools; 59 names… See the full description on the dataset page: https://huggingface.co/datasets/jensjepsen/danish-tool-dialogues-v6.danish-tool-dialogues-v7
danish-tool-dialogues-v1
Danish multi-turn tool-use conversations with reasoning, translated from the
Glaive subset of
Nanbeige/ToolMind
(Apache-2.0) by scripts/translate_toolmind_da.py.
Complements danish-tool-calls-v1, which is single-turn and synthetic. Here
the conversations run several turns, tool results are fed back, and the
assistant reasons before calling.
split
rows
train
17,160
eval_seen_tools
701
eval_unseen_tools
768
925 distinct tools; 59 names… See the full description on the dataset page: https://huggingface.co/datasets/jensjepsen/danish-tool-dialogues-v7.danish-tool-dialogues-v4
danish-tool-dialogues-v1
Danish multi-turn tool-use conversations with reasoning, translated from the
Glaive subset of
Nanbeige/ToolMind
(Apache-2.0) by scripts/translate_toolmind_da.py.
Complements danish-tool-calls-v1, which is single-turn and synthetic. Here
the conversations run several turns, tool results are fed back, and the
assistant reasons before calling.
split
rows
train
17,598
eval_seen_tools
762
eval_unseen_tools
772
932 distinct tools; 59 names… See the full description on the dataset page: https://huggingface.co/datasets/jensjepsen/danish-tool-dialogues-v4.kapibala-sales-dialogues
Kapibala Sales Dialogues
A sales-conversation dataset with outcome, conversation-level and sentence-level labels
🤗 Hugging Face · Annotation details · 中文
630 synthetic sales conversations (11,688 messages, Chinese and English, five domains) between an LLM-simulated customer and an AI salesperson. Every conversation carries three layers of labels, each produced by a single method across the whole dataset:
L1 — outcome. Did the customer buy, agree to a next step, stay undecided… See the full description on the dataset page: https://huggingface.co/datasets/Thomasgudan/kapibala-sales-dialogues.apptek_callcenter_dialogues_travel_hospitality_no_transcripts
AppTek Call-Center Dialogues — Travel and Hospitality (No Transcripts)
This is a filtered derivative of AppTek Call-Center Dialogues, prepared for a specific use case.
Changes from the source dataset
Restricted the dataset to the travel and hospitality domains.
Removed the transcript field (text) entirely.
Kept the original audio and the domain, gender, and accent metadata.
Preserved the source dataset's test split.
This dataset has transcripts removed and is… See the full description on the dataset page: https://huggingface.co/datasets/josemancharo/apptek_callcenter_dialogues_travel_hospitality_no_transcripts.empathetic_dialogues_v2Fine-tuned empathetic dialogue datasets from https://huggingface.co/datasets/empathetic_dialogues
With labeled chat history, system response, question or not and behavior.
empathetic_dialogues
Dataset Card for "empathetic_dialogues"
More Information needed
danish-tool-dialogues-v5
danish-tool-dialogues-v1
Danish multi-turn tool-use conversations with reasoning, translated from the
Glaive subset of
Nanbeige/ToolMind
(Apache-2.0) by scripts/translate_toolmind_da.py.
Complements danish-tool-calls-v1, which is single-turn and synthetic. Here
the conversations run several turns, tool results are fed back, and the
assistant reasons before calling.
split
rows
train
17,596
eval_seen_tools
762
eval_unseen_tools
772
932 distinct tools; 59 names… See the full description on the dataset page: https://huggingface.co/datasets/jensjepsen/danish-tool-dialogues-v5.doctor-patient_role-play_dialoguesJapanese-Roleplay-Dialogues
Japanese-Roleplay-Dialogues
This is a dialogue corpus collected from Japanese role-playing forum (commonly known as "なりきりチャット(narikiri chat)"). Each record corresponds to a single thread.
For the original version, no filtering has been applied.
For the filtered version, the following filtering and cleaning conditions have been applied:
If the number of unique poster in the posts of each record is 1 or less, delete the entire record.
If the length of the posts is 10 or less, delete… See the full description on the dataset page: https://huggingface.co/datasets/OmniAICreator/Japanese-Roleplay-Dialogues.english-daily-dialogues-10k
English Daily Dialogues 10K
A general-purpose, open dataset of 10,000 synthetic multi-turn English conversations spanning ten everyday-life domains. Built as a clean NLP resource for dialogue modeling, response generation, intent understanding, and conversational evaluation. This is a general language resource — not a safety or security benchmark.
Curated by Enes Deniz (ORCID 0009-0006-9491-3565), Co-Founder at AltaySec. It is the English companion to the Turkish Daily Dialogues… See the full description on the dataset page: https://huggingface.co/datasets/3nesdeniz/english-daily-dialogues-10k.rus_med_dialogues
Russian-language dataset of 2282 patient conversations in a medical bot.
The training sample includes 2053 conversations;
The test sample includes 229 conversations;
Feature characteristics:
topic - medical topic
context - user-ai message history
user_question - last user question
assistant_answer - ai answer according the context and topic
prompt - ready prompt for fincetuning instruct model (adapted for using with unsloth… See the full description on the dataset page: https://huggingface.co/datasets/Mykes/rus_med_dialogues.Discord-DialoguesThis is a clone of mookiezi/Discord-Dialogues.
Discord-Dialogues is a large-scale dataset of anonymized Discord conversations from late spring to early fall 2025 for training and evaluating realistic conversational AI models in a ChatML-friendly format.
This dataset contains 7.3 million exchanges spread out over 16 million turns, with more than 139 million words.
Features
Mixed single and multi-turn exchanges
Human-only dialogues (no bots)
Filtered for ToS and… See the full description on the dataset page: https://huggingface.co/datasets/aaronmoo12/Discord-Dialogues.KoCulture-Dialogues
Dataset Card for 한국어 신조어 대화 데이터셋 (Korean Neologism Dialogues Dataset)
This dataset card provides a comprehensive overview of the Korean Neologism Dataset, created by Hugging Face KREW.
Dataset Details
Dataset Description: 본 데이터셋은 최신 한국어 신조어, 유행어, 밈을 포함하여 대형 언어 모델(LLM)의 한국어 이해 및 생성 능력을 향상시키기 위해 구축되었습니다. 나무위키와 트렌드어워드 등에서 수집한 원시 자료를 바탕으로 여러 LLM을 활용해 초기 데이터를 생성한 후, Hugging Face KREW 참여자들이 직접 검수하고 정제했습니다.
Curated by: Hugging Face KREW (참여자: 유용상 (Yongsang Yoo), 김하림… See the full description on the dataset page: https://huggingface.co/datasets/huggingface-KREW/KoCulture-Dialogues.