datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
apex-r1-real-world-documents
Apex-R1 Real-World Benchmark Documents
This dataset stores real-world document/data assets collected for Apex-R1 synthetic long-horizon agentic RL workspace generation.
The files are intended as seed workspace materials, not as benchmark task labels. They can be injected into APEX-style filesystem/ or .apps_data/ environments to create more realistic and diverse professional-domain tasks.
Contents
benchmark_documents/
EnterpriseBench/ # CRM invoices… See the full description on the dataset page: https://huggingface.co/datasets/mtybilly/apex-r1-real-world-documents.RealWorldQuestioning
RealWorldQuestioning Benchmark
RealWorldQuestioning is a benchmark dataset of 400+ real-world user questions collected from public discussion forums (e.g., Reddit, Quora), designed to support evaluation of gender bias and information disparity in Large Language Models (LLMs). The dataset spans four business-relevant domains: Education, Jobs, Investment, and Health.
Each question is annotated with:
User persona (Male or Female framing)
Source forum
Domain category
Four anonymized… See the full description on the dataset page: https://huggingface.co/datasets/SonalPrabhune/RealWorldQuestioning.System-Prompt-Instruction-Real-world-Implementation-Training-set
SPIRIT Dataset (System Prompt Instruction Real-world Implementation Training-set)
Dataset Summary
SPIRIT is a high-quality system prompt instruction dataset designed to enhance language models' ability to follow complex system prompts. The dataset comprises real-world system prompts collected from GitHub repositories and synthetically generated conversations, specifically curated to improve system prompt adherence in large language models.
Dataset Creation… See the full description on the dataset page: https://huggingface.co/datasets/EricLu/System-Prompt-Instruction-Real-world-Implementation-Training-set.RealWorldQA_Kazakh_Russian
Dataset Summary
These are the machine-translated Kazakh and Russian versions of the RealWorldQA dataset. As a multimodal benchmark, RealWorldQA is specifically designed to evaluate the real-world spatial understanding and visual reasoning of models. Kazakh and Russian versions serve as a benchmark for evaluating how well models can understand physical environments, spatial relationships, and object attributes based on real-world images when prompted in Kazakh or Russian.… See the full description on the dataset page: https://huggingface.co/datasets/issai/RealWorldQA_Kazakh_Russian.innoduel-rlhf-real-world-human-preferences-sample
Real-World Human Pairwise Preferences — Public Sample
📦 This is a free, public sample of a commercial dataset.
It contains 1,350 rows curated for inspection. The full dataset has 1.5 million
human pairwise-preference decisions.
Full dataset: https://huggingface.co/datasets/NordosoftOy/innoduel-rlhf
Request access / licensing: see § Access to the full dataset — contact kari.nieminen@nordo.fi.
Use this sample to evaluate the data's quality, structure and… See the full description on the dataset page: https://huggingface.co/datasets/NordosoftOy/innoduel-rlhf-real-world-human-preferences-sample.coding-skill-real-world-needsSynthetic Data Distillation from GPT-4o mini for Latest Programming Skills Market Needs
real-world-medical-mistakes-dataset
Real-World Medical Mistakes Dataset
A curated dataset of 100 de-identified clinical reports from Internal Medicine and Emergency Departments, each containing a physician-inserted realistic medical error. Designed for training and evaluating AI systems that detect critical patient safety errors in clinical documentation.
Dataset Description
Overview
This dataset was created as part of the Clinipal project — an AI-powered clinical error detection system. Three… See the full description on the dataset page: https://huggingface.co/datasets/Vrda/real-world-medical-mistakes-dataset.