datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.knowchat-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.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.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.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.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.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.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.danish-tool-dialogues-v8
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-v8.danish-tool-dialogues-v3
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
17,354
eval_seen_tools
756
eval_unseen_tools
768
908 distinct tools; 58 names… See the full description on the dataset page: https://huggingface.co/datasets/jensjepsen/danish-tool-dialogues-v3.danish-tool-dialogues-v1
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
17,138
eval_seen_tools
740
eval_unseen_tools
769
903 distinct tools; 57 names… See the full description on the dataset page: https://huggingface.co/datasets/jensjepsen/danish-tool-dialogues-v1.danish-tool-dialogues-v2
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
17,354
eval_seen_tools
756
eval_unseen_tools
768
908 distinct tools; 58 names… See the full description on the dataset page: https://huggingface.co/datasets/jensjepsen/danish-tool-dialogues-v2.empathetic_dialogues
Dataset Card for "empathetic_dialogues"
Dataset Summary
Dataset from Towards Empathetic Open-domain Conversation Models: a New Benchmark and Dataset, but with parquet format.
Supported Tasks and Leaderboards
More Information Needed
Languages
More Information Needed
Dataset Structure
Data Instances
default
Size of downloaded dataset files: 28.02 MB
Size of the generated dataset: 25.13 MB
Total amount of disk used:… See the full description on the dataset page: https://huggingface.co/datasets/brianist/empathetic_dialogues.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/kapibala-ai/kapibala-sales-dialogues.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… See the full description on the dataset page: https://huggingface.co/datasets/Abhishekh13/Question-Anchored-Tutoring-Dialogues-2k.ru-stem-dialogues
Russian STEM Educational Dialogues
Описание
Синтетический датасет русскоязычных учебных диалогов по STEM-темам (математика, физика, химия,
биология, информатика, программирование, инженерия). Каждый диалог — реалистичное взаимодействие
между пользователем (школьник / студент / профессионал) и ассистентом.
Методология
Модель: Qwen/Qwen2.5-7B-Instruct (4-bit NF4 quantization, bitsandbytes)
Формат генерации: текстовый формат с разделителями… See the full description on the dataset page: https://huggingface.co/datasets/AtesiT/ru-stem-dialogues.mt-dialogues-100k-v2
Multi-turn medical dialogues — V2 (pass@k)
39,996 dialogues, same 100k preformatted cases and doctor/patient/records setup
as V1, but
generated with pass@k=4: a case is regenerated from scratch, graded with
Inspect's model_graded_fact, until the conclusion is graded correct or 4
attempts are spent. 30,234 dialogues (76%) end on a graded-correct
conclusion, roughly 2 attempts per case on average thanks to stopping as soon
as one succeeds.
Grading is self-graded (the same model… See the full description on the dataset page: https://huggingface.co/datasets/zacbrld/mt-dialogues-100k-v2.