datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
RoadmapBench
RoadmapBench
A benchmark for evaluating AI coding agents on multi-target, long-horizon software development tasks derived from open-source project version upgrades.
Overview
RoadmapBench contains 115 tasks spanning 17 open-source repositories across 5 programming languages (Python, TypeScript, Go, Rust, C++). Each task requires an agent to implement multiple interdependent features that correspond to a real version upgrade of the target project.
Quick Start… See the full description on the dataset page: https://huggingface.co/datasets/UnipatAI/RoadmapBench.alpaca-data-gpt4-chineserussian-road-signs
Датасет размеченных знаков
Датасет размеченных дорожных знаков для задач компьютерного зрения и детекции объектов.
Загрузка
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="Dognellaf/russian-road-signs",
repo_type="dataset",
local_dir="./russian-road-signs"
)
Описание
Датасет содержит размеченные вручную кадры из видеозаписей с российскими дорожными знаками. Разметка в формате YOLO.
Изображений: 43 851 (JPEG)… See the full description on the dataset page: https://huggingface.co/datasets/Dognellaf/russian-road-signs.RoadmapBench
RoadmapBench
A benchmark for evaluating AI coding agents on multi-target, long-horizon software development tasks derived from open-source project version upgrades.
Overview
RoadmapBench contains 115 tasks spanning 17 open-source repositories across 5 programming languages (Python, TypeScript, Go, Rust, C++). Each task requires an agent to implement multiple interdependent features that correspond to a real version upgrade of the target project.
Task Structure… See the full description on the dataset page: https://huggingface.co/datasets/benchmark-anon-2026/RoadmapBench.obstacles_on_the_road
Unified Obstacles Dataset для AssistEye
Unified Obstacles Dataset создан в рамках проекта AssistEye — мобильного приложения, помогающего слабовидящим и незрячим пользователям с помощью голосового управления и офлайн-детекции окружающих объектов.
Датасет использовался для дообучения модели YOLO11n для сценария «Что на пути?». Модель определяет восемь классов городских препятствий, важных для безопасного передвижения.
Краткое описание
Датасет содержит 4 103 изображения… See the full description on the dataset page: https://huggingface.co/datasets/Dderedor/obstacles_on_the_road.RoadSocial
About Dataset
This dataset accompanies the paper RoadSocial: A Diverse Dataset and Benchmark for Road Event Understanding from Social Video Narratives.
RoadSocial is a large-scale, diverse VideoQA dataset designed for generic road event understanding from social media narratives. It can help enhance the road event comprehension capabilities of general-purpose Video LLMs and improve their performance in traffic scene understanding, planning, and other autonomous vehicle (AV) related… See the full description on the dataset page: https://huggingface.co/datasets/chiragp26/RoadSocial.ChatHaruhi-RolePlaying
ChatHaruhi
Reviving Anime Character in Reality via Large Language Model
Chat-Haruhi-Suzumiyais a language model that imitates the tone, personality and storylines of characters like Haruhi Suzumiya,
https://github.com/LC1332/Chat-Haruhi-Suzumiya
Using this to load character and chat with him/her
from ChatHaruhi import ChatHaruhi
chatbot = ChatHaruhi( role_from_hf = "silk-road/ChatHaruhi-RolePlaying/haruhi",\
llm = 'openai' ,\… See the full description on the dataset page: https://huggingface.co/datasets/silk-road/ChatHaruhi-RolePlaying.Wizard-LM-Chinese-instruct-evolWizard-LM-Chinese是在MSRA的Wizard-LM数据集上，对指令进行翻译，然后再调用GPT获得答案的数据集
Wizard-LM包含了很多难度超过Alpaca的指令。
中文的问题翻译会有少量指令注入导致翻译失败的情况
中文回答是根据中文问题再进行问询得到的。
我们会陆续将更多数据集发布到hf，包括
Coco Caption的中文翻译
CoQA的中文翻译
CNewSum的Embedding数据
增广的开放QA数据
WizardLM的中文翻译
如果你也在做这些数据集的筹备，欢迎来联系我们，避免重复花钱。
骆驼(Luotuo): 开源中文大语言模型
https://github.com/LC1332/Luotuo-Chinese-LLM
骆驼(Luotuo)项目是由冷子昂 @ 商汤科技, 陈启源 @ 华中师范大学 以及 李鲁鲁 @ 商汤科技 发起的中文大语言模型开源项目，包含了一系列语言模型。
( 注意: 陈启源 正在寻找2024推免导师，欢迎联系 )
骆驼项目不是商汤科技的官方产品。
Citation… See the full description on the dataset page: https://huggingface.co/datasets/silk-road/Wizard-LM-Chinese-instruct-evol.roadmap-databasesroad-images-and-embeddings
Norwegian Road Images with Embeddings (Trondheim Area)
A dataset of 34,908 road images from the Trondheim region of Norway (~40km radius), captured by Statens vegvesen (Norwegian Public Roads Administration) in 2025. Each image is paired with rich geospatial metadata, nearest address information, and a 3072-dimensional image embedding from Google's gemini-embedding-2-preview model.
Dataset Structure
Each example contains:
Field
Type
Description
image
Image… See the full description on the dataset page: https://huggingface.co/datasets/thomasht86/road-images-and-embeddings.svge-uav-road-hazard-v0
SVGE UAV Road Hazard v0
SVGE UAV Road Hazard v0 is a small public research preview for photorealistic UAV road-inspection rare events.
The key signal is not just that the samples exist. The images are designed to look like field-like UAV inspection frames while still shipping with auditable masks, QA overlays, review crops, COCO annotations, and YOLO labels.
This package is not positioned as a benchmark, production detector, or full training corpus. It is a demand probe for one… See the full description on the dataset page: https://huggingface.co/datasets/kensou3/svge-uav-road-hazard-v0.ChatHaruhi-from-RoleLLMAdapt English Role in RoleBench into ChatHaruhi format
only using profiles part in ZenMoore/RoleBench
Great thanks to on authors of RoleLLM!
usage:
# if you pip installed chatharuhi it should be
# from chatharuhi import ChatHaruhi
from ChatHaruhi import ChatHaruhi
chatbot = ChatHaruhi( role_from_hf = 'silk-road/ChatHaruhi-from-RoleLLM/Sherlock Holmes', \
llm = 'openai',
embedding = 'bge_en')
response = chatbot.chat(role='Police Chief', text = 'Oh… See the full description on the dataset page: https://huggingface.co/datasets/silk-road/ChatHaruhi-from-RoleLLM.Road-Objects-Detection-Dataset
🚦 Road Object Detection Dataset (YOLOv8)
A multi-class road scene object detection dataset for training and benchmarking modern object detection models.
📌 Overview
This dataset contains annotated road scene images in YOLOv8 format for multi-class object detection.
It is suitable for developing and evaluating deep learning models for:
🚗 Vehicle Detection
🚦 Traffic Monitoring
🏙️ Smart City Applications
🚘 Autonomous Driving Research
📹 Intelligent… See the full description on the dataset page: https://huggingface.co/datasets/SobanHM/Road-Objects-Detection-Dataset.UK-Road-Bend-ClassificationChatHaruhi-54K-Role-Playing-Dialogue
ChatHaruhi
Reviving Anime Character in Reality via Large Language Model
github repo: https://github.com/LC1332/Chat-Haruhi-Suzumiya
Chat-Haruhi-Suzumiyais a language model that imitates the tone, personality and storylines of characters like Haruhi Suzumiya,
The project was developed by Cheng Li, Ziang Leng, Chenxi Yan, Xiaoyang Feng, HaoSheng Wang, Junyi Shen, Hao Wang, Weishi Mi, Aria Fei, Song Yan, Linkang Zhan, Yaokai Jia, Pingyu Wu, and Haozhen Sun,etc.
This… See the full description on the dataset page: https://huggingface.co/datasets/silk-road/ChatHaruhi-54K-Role-Playing-Dialogue.Unified_Road_Defect_Dataset
Unified Road Defect Dataset
A merged, YOLO-format road-defect detection dataset that combines RDD-2022
(primary, ground-level, 6 countries) with two supplementary aerial/drone
datasets — UAV-PDD2023 (China) and RoadDamageVision (China + Spain) —
into a single 4-class CRDDC schema.
This is a derived dataset. It re-packages and re-labels images from three
independently published sources. All credit for the underlying images and
original annotations belongs to their respective… See the full description on the dataset page: https://huggingface.co/datasets/TamAko783/Unified_Road_Defect_Dataset.street-smart-road-signs
Street Smart: Road Sign Recognition
Dataset Summary
A public, viewer-ready educational challenge dataset. Host-only scoring data and hidden targets are excluded.
Splits
Split
Examples
Description
train
701
Labeled training data
test
176
Public inputs with withheld target labels or annotations
Data Fields
Field
Type
image
Image
image_id
string
width
int64
height
int64
objects.bbox… See the full description on the dataset page: https://huggingface.co/datasets/hoangbang/street-smart-road-signs.test_roadworkRoad-Objects-Detection-Dataset
🚦 Road Object Detection Dataset (YOLOv8)
A multi-class road scene object detection dataset for training and benchmarking modern object detection models.
📌 Overview
This dataset contains annotated road scene images in YOLOv8 format for multi-class object detection.
It is suitable for developing and evaluating deep learning models for:
🚗 Vehicle Detection
🚦 Traffic Monitoring
🏙️ Smart City Applications
🚘 Autonomous Driving Research
📹 Intelligent… See the full description on the dataset page: https://huggingface.co/datasets/Tharun2307/Road-Objects-Detection-Dataset.road-distress-seg-1280
Road Pavement Distress — YOLO11-seg (3 class)
Instance-segmentation dataset for road pavement distress, in YOLO segmentation
format (one .txt per image with class x1 y1 x2 y2 ... normalized polygon points).
Classes
id
name
0
crack
1
joint
2
patching
Splits
split
images
train
5354
valid
277
test
190
Layout
data.yaml
train/ images/ labels/
valid/ images/ labels/
test/ images/ labels/… See the full description on the dataset page: https://huggingface.co/datasets/Kuerser/road-distress-seg-1280.chinese-dolly-15kChinese-Dolly-15k是骆驼团队翻译的Dolly instruction数据集
最后49条数据因为翻译长度超过限制，没有翻译成功，建议删除或者手动翻译一下
原来的数据集'databricks/databricks-dolly-15k'是由数千名Databricks员工根据InstructGPT论文中概述的几种行为类别生成的遵循指示记录的开源数据集。这几个行为类别包括头脑风暴、分类、封闭型问答、生成、信息提取、开放型问答和摘要。
在知识共享署名-相同方式共享3.0（CC BY-SA 3.0）许可下，此数据集可用于任何学术或商业用途。
我们会陆续将更多数据集发布到hf，包括
Coco Caption的中文翻译
CoQA的中文翻译
CNewSum的Embedding数据
增广的开放QA数据
WizardLM的中文翻译
MMC4的中文翻译
如果你也在做这些数据集的筹备，欢迎来联系我们，避免重复花钱。
骆驼(Luotuo): 开源中文大语言模型
https://github.com/LC1332/Luotuo-Chinese-LLM… See the full description on the dataset page: https://huggingface.co/datasets/silk-road/chinese-dolly-15k.road_detectHaruhi-Zero
用于ChatHaruhi-Zero Extend的训练数据
目前还不知道数据规模 知道的话回头会更名为Haruhi-Zero-XXX K
目前只放出每个source的sample，完整的数据将在1.0 模型放出之后发布
主项目链接 https://github.com/LC1332/Chat-Haruhi-Suzumiya
如果有兴趣加入我们的训练请联系chengli.thu@gmail.com
计划加入的数据源
数据源
中文小说数据
erotics小说数据
ChatHaruhi 52K, （转了message格式）
Chinese 13.2k, 转了message格式）
Waifu-extended 0.2K, 看看方不方便转成message格式，不行就简单的user-AI
Claude-Baize数据 7.2K
PIPPA数据 1.68K JanitorAI数据
PIPPA翻译数据
RoleLLM 1.6K, 看看方不方便转成message格式，不行就简单的user-AI
0.2
进一步去掉AI助理的相关数据… See the full description on the dataset page: https://huggingface.co/datasets/silk-road/Haruhi-Zero.roadworkroadsign-judged-ensemble-agree1
Box-overlay preview
Auto-generated sample of the labelled boxes (with judge scores when available). Regenerated on every push.
ChatHaruhi_NovelWritingroadwork2road-hazards-datasetdata-road_network_eta
Korea Road Network ETA (v3)
16개 광역지자체 도로망 그래프. 시간대별 평균 통행속도(p50)가 부착되어 있어
ETA(예상소요시간) 산정·라우팅·배차 시뮬레이션에 바로 사용 가능합니다.
Contents
각 region 마다 self-contained 파일 두 개:
{region}_osm_v3_nodes.parquet — 노드 (node_id, lat, lon)
{region}_osm_v3_edges.parquet — 엣지 (source, target, length_m,
highway, oneway, ktdb_matched, …, 시간대별 속도 컬럼)
Regions (16)
seoul, busan, daegu, incheon, gwangju, daejeon, ulsan, sejong,
gyeonggi, gangwon, chungbuk, chungnam, jeonbuk… See the full description on the dataset page: https://huggingface.co/datasets/CAMUS-LAB/data-road_network_eta.ZOD-Mini-2D-Road-Scenes
ZOD-Mini-2D-Road-Scenes
The ZOD-Mini-2D-Road-Scenes dataset is derived from the Zenseact Open Dataset (ZOD), property of Zenseact AB (© 2022 Zenseact AB), and is licensed under the permissive CC BY-SA 4.0. Any public use, distribution, or display of this dataset must contain this entire notice:
For this dataset, Zenseact AB has taken all reasonable measures to remove all personally identifiable information, including faces and license plates. To the extent that you like to request… See the full description on the dataset page: https://huggingface.co/datasets/8bits-ai/ZOD-Mini-2D-Road-Scenes.