datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
WebVidWebLINX-full
WebLINX: Real-World Website Navigation with Multi-Turn Dialogue
WARNING: This is not the main WebLINX data card! You might want to use the main WebLINX data card instead:
WebLINX: Real-World Website Navigation with Multi-Turn Dialogue
WebLINX: Real-World Website Navigation with Multi-Turn Dialogue
Xing Han Lù*, Zdeněk Kasner*, Siva Reddy
💾Code
📄Paper
🌐Website
📓Colab
🤖Models
💻Explorer
🐦Tweets
🏆Leaderboard
Your browser does not support the… See the full description on the dataset page: https://huggingface.co/datasets/McGill-NLP/WebLINX-full.WEB-Dataset
WorldEngine Bimanual Dataset for Post-training
A large-scale, language-annotated real-robot bimanual manipulation dataset for
post-training robotics foundation models. It spans 90 everyday manipulation tasks
collected with a bimanual YAM follower arm teleoperated by a GELLO leader,
recording joint state, action, and three synchronized camera streams at 60 Hz.
Shared lineage, different story. This dataset shares its hardware, teleoperation
setup, and recording pipeline with the… See the full description on the dataset page: https://huggingface.co/datasets/WorldEngineAI/WEB-Dataset.Edge-Agent-Reasoning-WebSearch-260K
Edge Agent Reasoning WebSearch 260K
Abstract
The Edge-Agent-Reasoning-WebSearch-260K dataset is a massive, synthetically expert-engineered corpus of over 700 Million tokens, designed to train small, local models (SLMs) and edge-deployed agents in advanced problem deconstruction and self-aware reasoning.
Rather than training a model to execute instructions directly—which often leads to hallucinations when context is missing—this dataset trains a model to act as a… See the full description on the dataset page: https://huggingface.co/datasets/yatin-superintelligence/Edge-Agent-Reasoning-WebSearch-260K.causvid_websitewebsite-media
OpenRAL — website media
Video clips shown in the "See it run" section of openral.com
(benchmarks, simulation and on-hardware deployment runs).
Each clip lives under <category>/<benchmark>_<rskill>_<success|fail>/ with three
web-optimised assets:
poster.jpg — first-frame thumbnail
preview.mp4 — square 640px, muted (the autoscroll strip)
full.mp4 — native aspect, ≤1080p, with audio (the expand modal)
Generated and published by scripts/build-media.mjs in the
website repo.… See the full description on the dataset page: https://huggingface.co/datasets/OpenRAL/website-media.Edge-Agent-Reasoning-WebSearch-260K
Edge Agent Reasoning WebSearch 260K
Abstract
The Edge-Agent-Reasoning-WebSearch-260K dataset is a massive, synthetically expert-engineered corpus of over 700 Million tokens, designed to train small, local models (SLMs) and edge-deployed agents in advanced problem deconstruction and self-aware reasoning.
Rather than training a model to execute instructions directly—which often leads to hallucinations when context is missing—this dataset trains a model to act as a… See the full description on the dataset page: https://huggingface.co/datasets/BlueIsGreen/Edge-Agent-Reasoning-WebSearch-260K.gemma-4-e4b-webvid-4K
gemma-4-e4b-webvid-4K
This dataset contains the webvid_upgraded.json annotations and the videos referenced by that file.
Source: https://huggingface.co/datasets/OpenGVLab/VideoChat2-IT/tree/main/video/vqa/webvid_qa.
Files
webvid_upgraded.json: upgraded WebVid QA/action annotations.
videos/: MP4 files referenced by webvid_upgraded.json.
All video paths in webvid_upgraded.json are relative to the dataset root and point into videos/, for example… See the full description on the dataset page: https://huggingface.co/datasets/bear7011/gemma-4-e4b-webvid-4K.Edge-Agent-Reasoning-WebSearch-260K
Edge Agent Reasoning WebSearch 260K
Abstract
The Edge-Agent-Reasoning-WebSearch-260K dataset is a massive, synthetically expert-engineered corpus of over 700 Million tokens, designed to train small, local models (SLMs) and edge-deployed agents in advanced problem deconstruction and self-aware reasoning.
Rather than training a model to execute instructions directly—which often leads to hallucinations when context is missing—this dataset trains a model to act as a… See the full description on the dataset page: https://huggingface.co/datasets/DEMIRUNC/Edge-Agent-Reasoning-WebSearch-260K.WebVisualizerWebUOT-238-Test
Dataset Card for WebUOT-238-Test
This is a FiftyOne dataset with 238 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("Voxel51/WebUOT-238-Test")
# Launch the App
session = fo.launch_app(dataset)
Dataset Description… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/WebUOT-238-Test.Edge-Agent-Reasoning-WebSearch-260K
Edge Agent Reasoning WebSearch 260K
Abstract
The Edge-Agent-Reasoning-WebSearch-260K dataset is a massive, synthetically expert-engineered corpus of over 700 Million tokens, designed to train small, local models (SLMs) and edge-deployed agents in advanced problem deconstruction and self-aware reasoning.
Rather than training a model to execute instructions directly—which often leads to hallucinations when context is missing—this dataset trains a model to act as a… See the full description on the dataset page: https://huggingface.co/datasets/Torenn/Edge-Agent-Reasoning-WebSearch-260K.RelitLRM_Webwebpagewebsiteedge-agent-reasoning-websearch-260k
Edge Agent Reasoning WebSearch 260K
Abstract
The Edge-Agent-Reasoning-WebSearch-260K dataset is a massive, synthetically expert-engineered corpus of over 700 Million tokens, designed to train small, local models (SLMs) and edge-deployed agents in advanced problem deconstruction and self-aware reasoning.
Rather than training a model to execute instructions directly—which often leads to hallucinations when context is missing—this dataset trains a model to act as a… See the full description on the dataset page: https://huggingface.co/datasets/ppenner/edge-agent-reasoning-websearch-260k.so101_main_bin_2cameras_webThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "so101_follower",
"total_episodes": 53,
"total_frames": 9844,
"total_tasks": 1,
"total_videos": 106,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 30,
"splits": {
"train": "0:53"
},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/guanfengliu/so101_main_bin_2cameras_web.WebVR
WebVR
WebVR: Benchmarking Multimodal LLMs for WebPage Recreation from Videos via Human-Aligned Visual Rubrics
[Paper] [Project Page] [Code]
WebVR is a research benchmark for evaluating whether multimodal language models can recreate webpages from videos. The dataset is designed for academic evaluation of webpage reconstruction quality, with paired webpage artifacts, recorded webpage videos, image assets, and rubric-based annotations aligned to each sample.
Benchmark… See the full description on the dataset page: https://huggingface.co/datasets/BroAlanTaps/WebVR.Edge-Agent-Reasoning-WebSearch-260K
Edge Agent Reasoning WebSearch 260K
Abstract
The Edge-Agent-Reasoning-WebSearch-260K dataset is a massive, synthetically expert-engineered corpus of over 700 Million tokens, designed to train small, local models (SLMs) and edge-deployed agents in advanced problem deconstruction and self-aware reasoning.
Rather than training a model to execute instructions directly—which often leads to hallucinations when context is missing—this dataset trains a model to act as a… See the full description on the dataset page: https://huggingface.co/datasets/JACKYS999/Edge-Agent-Reasoning-WebSearch-260K.Agent-Reasoning-WebSearch-260K
Edge Agent Reasoning WebSearch 260K
Abstract
The Edge-Agent-Reasoning-WebSearch-260K dataset is a massive, synthetically expert-engineered corpus of over 700 Million tokens, designed to train small, local models (SLMs) and edge-deployed agents in advanced problem deconstruction and self-aware reasoning.
Rather than training a model to execute instructions directly—which often leads to hallucinations when context is missing—this dataset trains a model to act as a… See the full description on the dataset page: https://huggingface.co/datasets/kanepi-1977/Agent-Reasoning-WebSearch-260K.web-camera-face-liveness-detection
Web Camera Face Liveness Detection
The dataset consists of videos featuring individuals wearing various types of masks. Videos are recorded under different lighting conditions and with different attributes (glasses, masks, hats, hoods, wigs, and mustaches for men).
The dataset is created on the basis of iBeta Level 1 Dataset
In the dataset, there are 7 types of videos filmed on a web camera:
Silicone Mask - demonstration of a silicone mask attack (silicone)
2D mask with… See the full description on the dataset page: https://huggingface.co/datasets/UniqueData/web-camera-face-liveness-detection.duplo-pick-and-place-yellow-640x480-3-camerasThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"action": {
"dtype": "float32",
"shape": [
6
],
"names": [
"shoulder_pan.pos",
"shoulder_lift.pos",
"elbow_flex.pos",
"wrist_flex.pos",
"wrist_roll.pos",
"gripper.pos"… See the full description on the dataset page: https://huggingface.co/datasets/webstep/duplo-pick-and-place-yellow-640x480-3-cameras.Dense-WebVid-CoVREdge-Agent-Reasoning-WebSearch-260K
Edge Agent Reasoning WebSearch 260K
Abstract
The Edge-Agent-Reasoning-WebSearch-260K dataset is a massive, synthetically expert-engineered corpus of over 700 Million tokens, designed to train small, local models (SLMs) and edge-deployed agents in advanced problem deconstruction and self-aware reasoning.
Rather than training a model to execute instructions directly—which often leads to hallucinations when context is missing—this dataset trains a model to act as a… See the full description on the dataset page: https://huggingface.co/datasets/svryn/Edge-Agent-Reasoning-WebSearch-260K.website_assetsso101_main_bin_2cameras_web2This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "so101_follower",
"total_episodes": 43,
"total_frames": 13165,
"total_tasks": 1,
"total_videos": 86,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 30,
"splits": {
"train": "0:43"
},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/guanfengliu/so101_main_bin_2cameras_web2.push_purple_block_webcamchocopan-reverse-oracle-webWebVid-CoVRarxiv.org/abs/2308.14746
web-camera-people-behavior
Web Camera People Behavior Dataset for computer vision tasks
Dataset includes 2,300+ individuals, contributing to a total of 53,800+ videos and 9,300+ images captured via webcams. It is designed to study social interactions and behaviors in various remote meetings, including video calls, video conferencing, and online meetings.
By leveraging this dataset, developers and researchers can enhance their understanding of human behavior in digital communication settings, contributing… See the full description on the dataset page: https://huggingface.co/datasets/UniDataPro/web-camera-people-behavior.