datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
MME-RealWorld-Base64
MME-RealWorld Dataset
This dataset contains multiple JSON files split into chunks. It includes information such as questions, images encoded in base64, and other related metadata.
Usage
You can load the dataset using the datasets library:
from datasets import load_dataset
dataset = load_dataset('yifanzhang114/MME-RealWorld-Base64', data_dir='MME-RealWorld')
dataset = load_dataset('yifanzhang114/MME-RealWorld-Base64', data_dir='MME-RealWorld-CN')
## the image can be… See the full description on the dataset page: https://huggingface.co/datasets/yifanzhang114/MME-RealWorld-Base64.real_world_data_annotated
Real-World Data — Camera-3 Annotations
This dataset provides perception annotations for 1,000 real robot demonstration
episodes across five tasks. It is the annotation companion to
mzxuan/real_world_data,
which contains the original recordings.
Download both datasets for visual robot-learning experiments. This repository
does not contain the original RGB, depth, robot state, or action commands. It
contains masks, object identities and roles, 2D/3D boxes, annotation-only HDF5… See the full description on the dataset page: https://huggingface.co/datasets/mzxuan/real_world_data_annotated.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.real-world-multimodal-field-sample
Origin Data Lab --- Real-World Multimodal Field Sample
A compact technical sample demonstrating Origin Data Lab's real-world
field data collection and structured data-operations workflow.
Capture → Metadata / IMU → Validation → QC → Privacy Processing →
Structured Delivery
This public repository is intentionally limited in scope. It is designed
to provide verifiable evidence of our workflow without publishing
sensitive raw footage, contributor-identifying information, precise… See the full description on the dataset page: https://huggingface.co/datasets/origindatalab/real-world-multimodal-field-sample.AItuber-Realworld-Data-beta1
AItuber Realworld Chat Dataset
概要
本データセットは、AItuber（AI VTuber）の 配信チャット会話データ を合成的に生成したものです。AItuberペルソナデータと nvidia/Nemotron-Personas-Japan のユーザーペルソナを入力に、複数の視聴者がコメントし、AItuberが応答する4ターンのリアルな配信チャットデータを生成しています。生成にはSDG-Nexusという合成データ生成パイプラインを用いました。（sdg-nexus）
データの説明
項目
内容
件数
1,946件
形式
JSONL（1行1JSON）
言語
日本語
生成日
2026年3月
ライセンス
odc-by ( Open Data Commons Attribution License )… See the full description on the dataset page: https://huggingface.co/datasets/DataPilot/AItuber-Realworld-Data-beta1.TRM_Genesis_RealWorld_40k
TRM_Genesis_RealWorld_40k
Developer / Brand: Within Us AI
A TRM (Tiny Recursive Model) dataset upgraded for real-world truth:
Every example is fact-based Q&A
Each answer includes fact_sources (citations) and a verification tag
Prompts remain TRM-native: short, constraint-aware, and optimized for tiny contexts
Size
40000 examples (JSONL)
Schema
Each line is a JSON object:
prompt.messages: chat prompt (Question)
response: factual Answer… See the full description on the dataset page: https://huggingface.co/datasets/11-47/TRM_Genesis_RealWorld_40k.realworld-qa
Real World Records — Evaluation Dataset (QA pairs) + Coverage Summary
TL;DR
A publication-ready evaluation dataset for a Real World Studios ML system, delivered as JSONL (one JSON object per line with input, target, source). It covers Real World Records label/studio/WOMAD history, Peter Gabriel's full discography, and a broad cross-section of the label's artist catalogue with verified catalogue numbers, dates, producers, and collaborations.
Every answer is grounded in a named… See the full description on the dataset page: https://huggingface.co/datasets/rw-robai/realworld-qa.Reindex-Then-Adapt-Real-World-Datacoding-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.TRM_Genesis_RealWorld_5k
TRM_Genesis_RealWorld_5k
Developer / Brand: Within Us AI
A TRM (Tiny Recursive Model) dataset upgraded for real-world truth:
Every example is fact-based Q&A
Each answer includes fact_sources (citations) and a verification tag
Prompts remain TRM-native: short, constraint-aware, and optimized for tiny contexts
Size
5000 examples (JSONL)
Schema
Each line is a JSON object:
prompt.messages: chat prompt (Question)
response: factual Answer… See the full description on the dataset page: https://huggingface.co/datasets/11-47/TRM_Genesis_RealWorld_5k.TRM_Genesis_RealWorld_1k
TRM_Genesis_RealWorld_1k
Developer / Brand: Within Us AI
A TRM (Tiny Recursive Model) dataset upgraded for real-world truth:
Every example is fact-based Q&A
Each answer includes fact_sources (citations) and a verification tag
Prompts remain TRM-native: short, constraint-aware, and optimized for tiny contexts
Size
1000 examples (JSONL)
Schema
Each line is a JSON object:
prompt.messages: chat prompt (Question)
response: factual Answer… See the full description on the dataset page: https://huggingface.co/datasets/11-47/TRM_Genesis_RealWorld_1k.TRM_Genesis_RealWorld_15k
TRM_Genesis_RealWorld_15k
Developer / Brand: Within Us AI
A TRM (Tiny Recursive Model) dataset upgraded for real-world truth:
Every example is fact-based Q&A
Each answer includes fact_sources (citations) and a verification tag
Prompts remain TRM-native: short, constraint-aware, and optimized for tiny contexts
Size
15000 examples (JSONL)
Schema
Each line is a JSON object:
prompt.messages: chat prompt (Question)
response: factual Answer… See the full description on the dataset page: https://huggingface.co/datasets/11-47/TRM_Genesis_RealWorld_15k.humanoid-realworld-signal-processor
Humanoid Real-World Signal Processor
A signal processing agent specialized in interpreting
real-world sensor streams for humanoid decision systems.
Designed to transform raw environmental input
into structured actionable insights.
Capabilities
Multi-sensor signal parsing
Noise filtering logic
Structured data extraction
Real-time signal interpretation
Applications
Industrial humanoids
Environmental monitoring robots
Smart infrastructure agents
Autonomous… See the full description on the dataset page: https://huggingface.co/datasets/ariefansclub/humanoid-realworld-signal-processor.real_world_quant_reasoning_v1