datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
HalluTruthQA-4K
HalluTruthQA-4K
HalluTruthQA-4K is the official data release for Subtask 2.2 ("Hallucination Detection and Find the Truth") of the HalluScoring 2026 shared task, hosted at ArabicNLP 2026. It extends the HalluTruthQA benchmark from 2,400 to 4,000 expert-annotated Arabic question-answering instances across four knowledge-intensive domains.
Dataset Summary
The full corpus is 4,000 Arabic question-answering instances, exactly balanced across four domains (1,000… See the full description on the dataset page: https://huggingface.co/datasets/Bekhouche/HalluTruthQA-4K.GLM-4-Instruct-4K-zh
Dataset Card for Dataset Name
❤️欢迎使用rqq/GLM-4-Instruct-4K-zh数据集，本数据集包含了4000条高质量的glm4回复。
该数据集的提问数据源自高质量的Sao10K/Claude-3-Opus-Instruct-5K数据集，我们把它的问题翻译成了中文，使用glm-4进行了重新回答。
该数据集使用alpaca格式，可以直接用在llama-factory项目中进行训练！
文件如下：
GLM-4-Instruct-4K-zh.json 问答数据集，alpaca格式
GLM-4-question-translate-5K-zh 翻译-对话数据集，记录了把Sao10K/Claude-3-Opus-Instruct-5K问题翻译成中文的数据
Welcome to the rqq/GLM-4-Instruct-4K-zh dataset! This dataset includes 4,000 high-quality responses from the GLM-4 model.
The question data… See the full description on the dataset page: https://huggingface.co/datasets/rqq/GLM-4-Instruct-4K-zh.grpo-4k-reasoning-tools
🧠 GRPO 4K Reasoning Tools
A compact, high-quality dataset designed to train and evaluate reasoning-capable LLMs with tool usage and function calling. This dataset focuses on structured thinking, multi-step reasoning, and practical tool integration across diverse NLP tasks.
📌 Overview
GRPO 4K Reasoning Tools is a curated dataset of ~4K examples that combines:
🧩 Step-by-step reasoning (“thinking” traces)
🛠️ Tool usage / function calling patterns
🧠 Multi-task learning… See the full description on the dataset page: https://huggingface.co/datasets/nphearum/grpo-4k-reasoning-tools.RS-EoT-4K
Asking like Socrates: RS-EoT-4K Dataset
🌐 Project Website | 💻 GitHub Repository | 📄 Paper (ArXiv) | 🤗 Model (RS-EoT-7B)
📖 Introduction
RS-EoT-4K is a multimodal instruction-tuning dataset specifically designed to instill Evidence-of-Thought (EoT) reasoning capabilities into Vision-Language Models (VLMs) for Remote Sensing (RS) tasks.
This dataset was introduced in the paper "Asking like Socrates: Socrates helps VLMs understand remote sensing images". To… See the full description on the dataset page: https://huggingface.co/datasets/ShaoRun/RS-EoT-4K.hans-sft-4k
Hans-SFT-4K · SFT recipe for the audio-visual Clever Hans
Supervised fine-tuning (SFT) data accompanying the paper
When Vision Speaks for Sound.
Like the original Clever Hans —
the horse that looked like he could do arithmetic but was actually reading
his trainer's body language — video-capable MLLMs often look like they
can hear: they answer audio questions by reading visual cues and never
verifying the audio stream.
Hans-SFT-4K is the 3,834-sample SFT mix that teaches models to… See the full description on the dataset page: https://huggingface.co/datasets/Rakancorle1/hans-sft-4k.PyMath-AgentRL-4K
🧮 PyMath-AgentRL-4K
A supervised fine-tuning (SFT) dataset for training language models to solve mathematical problems using Python code interpreters.
Overview
Total Examples: 4,000 (deduplicated)
Format: Parquet
Language: English
License: Apache 2.0
Source Datasets
Merged from two high-quality sources:
Gen-Verse/Open-AgentRL-SFT-3K (3,000 examples)
JoeYing/ReTool-SFT (2,000 examples)
Deduplication: 20% overlap removed (1,000 duplicates)
Key… See the full description on the dataset page: https://huggingface.co/datasets/SimonSun/PyMath-AgentRL-4K.skolkovo-coaching-qa-4k
Skolkovo Executive Coaching Q&A Dataset
Описание
Датасет Q&A пар для обучения ИИ-коуча по программе Executive Coaching от Skolkovo.
Размер: 3,901 пар (893 оригинальных + 3,008 augmented)
Источники:
Административные документы Skolkovo
Лекции по коучингу
Книги по коучингу и лидерству (18 книг)
Кейсы и практические материалы
Структура данных
{
"question": "Как мотивировать команду?",
"answer": "Для мотивации команды важно...",
"role": "coach",
"source":… See the full description on the dataset page: https://huggingface.co/datasets/Ocheretny/skolkovo-coaching-qa-4k.rag-grounding-dpo-4k
RAG Grounding DPO Pairs (4K)
DPO preference pairs for training LLMs to faithfully use retrieved context in RAG pipelines.
Motivation
RAG is the dominant LLM deployment pattern in production. The core failure mode: models that ignore retrieved context and hallucinate answers, or that contradict documents with confidently-stated fabrications. This dataset trains models to ground answers in provided context.
Dataset Description
4,000 preference pairs… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/rag-grounding-dpo-4k.Databricks-Dolly-4k
Databricks-Dolly-4k
The resulting dataset contains 4000 samples of the databricks/databricks-dolly-15k dataset.
This split of an even smaller subset is provided for very fast experimentation and evaluation of models when computational resources are highly limited or for quick prototyping.
Dataset Structure
The dataset is provided as a DatasetDict with the following splits:
train: Contains 4000 samples.
Each split contains the following features, identical to the… See the full description on the dataset page: https://huggingface.co/datasets/Vishva007/Databricks-Dolly-4k.