datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.Wake-Vision
Dataset Card for Wake Vision
Dataset Description
"Wake Vision" is a large, high-quality dataset featuring over 6 million images, significantly exceeding the scale and diversity of
current tinyML datasets (100x). This dataset includes images with annotations of whether each image contains a person. Additionally,
it incorporates a comprehensive fine-grained benchmark to assess fairness and robustness, covering perceived gender, perceived age,
subject distance, lighting… See the full description on the dataset page: https://huggingface.co/datasets/Harvard-Edge/Wake-Vision.Prostate-Anatomical-Edge-Cases
Prostate-Anatomical-Edge-Cases
Stress-Testing Pelvic Autosegmentation Algorithms Using Anatomical Edge Cases —
a TCIA collection of pelvic radiotherapy planning CT with manually contoured
organs at risk, curated so that most cases contain anatomy known to break
autosegmentation algorithms (Kanwar et al., Phys Imaging Radiat Oncol 2023).
Read before using — the name is misleading in two ways:
This is CT, not MRI. Despite "Prostate" in the name it is not a prostate
mpMRI/zonal… See the full description on the dataset page: https://huggingface.co/datasets/MedOtter/Prostate-Anatomical-Edge-Cases.Wake-Vision-Train-LargeEdge-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.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.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.tiger_layer_edgesAn unofficial re-packaged parquet files of TIGER/Line® Edges data provided by the US Census Bureau.
See LICENSE.pdf for more details.
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/ppenner/edge-agent-reasoning-websearch-260k.domain-resurrect-edges
Dataset Card for domain-resurrect-edges
This dataset contains link counts between domains on the Internet. The data is based on CommonCrawl.
See mbrt/domain-resurrect for the companion dataset with scored domains based on Page Rank, and
the Blog post on how this was computed.
Dataset Details
Dataset Description
This dataset is a processed version of the CommonCrawl September crawl.
Each row is the count of how many hyperlinks exist between the source… See the full description on the dataset page: https://huggingface.co/datasets/mbrt/domain-resurrect-edges.kg-edges
Dataset Card for Every Cure Integrated Knowledge Graph (Edges)
Dataset Summary
The Every Cure KG is currently (as of February 2026) essentially an integrated, simplified and filtered merged KG comprising ROBOKOP and RTX-KG2.
The "Edges" dataset contains the records for all edges in the graph, including metadata.
See nodes dataset for the corresponding set of nodes.
Source Data
Attribution
First-level knowledge sources
Primary knowledge sources… See the full description on the dataset page: https://huggingface.co/datasets/everycure/kg-edges.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.record-EdgeThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "so100_follower",
"total_episodes": 60,
"total_frames": 20252,
"total_tasks": 1,
"total_videos": 60,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 30,
"splits": {
"train": "0:60"
},
"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/U-RIL/record-Edge.edges2shoes
Citation
@article{pix2pix2017,
title={Image-to-Image Translation with Conditional Adversarial Networks},
author={Isola, Phillip and Zhu, Jun-Yan and Zhou, Tinghui and Efros, Alexei A},
journal={CVPR},
year={2017}
}
demo_grab_pcb_from_edge_igor1_pcbcrop1This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "sam_evt2",
"total_episodes": 51,
"total_frames": 22668,
"total_tasks": 1,
"total_videos": 204,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 30,
"splits": {
"train": "0:51"
},
"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/1g0rrr/demo_grab_pcb_from_edge_igor1_pcbcrop1.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/svryn/Edge-Agent-Reasoning-WebSearch-260K.summit_grab_pcb_from_edge_centerThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "sam_evt2",
"total_episodes": 52,
"total_frames": 19092,
"total_tasks": 1,
"total_videos": 208,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 30,
"splits": {
"train": "0:52"
},
"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/1g0rrr/summit_grab_pcb_from_edge_center.record-edge_20260910_104144This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"action": {
"dtype": "float32",
"names": [
"shoulder_pan.pos",
"shoulder_lift.pos",
"elbow_flex.pos",
"wrist_flex.pos",
"wrist_roll.pos",
"gripper.pos"
],
"shape": [
6… See the full description on the dataset page: https://huggingface.co/datasets/Tron-Hayato/record-edge_20260910_104144.record-edge_20260910_103204This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"action": {
"dtype": "float32",
"names": [
"shoulder_pan.pos",
"shoulder_lift.pos",
"elbow_flex.pos",
"wrist_flex.pos",
"wrist_roll.pos",
"gripper.pos"
],
"shape": [
6… See the full description on the dataset page: https://huggingface.co/datasets/Tron-Hayato/record-edge_20260910_103204.edges2handbagsrecord-act-finetuned-base-edgeThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"action": {
"dtype": "float32",
"names": [
"shoulder_pan.pos",
"shoulder_lift.pos",
"elbow_flex.pos",
"wrist_flex.pos",
"wrist_roll.pos",
"gripper.pos"
],
"shape": [
6… See the full description on the dataset page: https://huggingface.co/datasets/Tron-Hayato/record-act-finetuned-base-edge.record-edge_20260910_094624This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"action": {
"dtype": "float32",
"names": [
"shoulder_pan.pos",
"shoulder_lift.pos",
"elbow_flex.pos",
"wrist_flex.pos",
"wrist_roll.pos",
"gripper.pos"
],
"shape": [
6… See the full description on the dataset page: https://huggingface.co/datasets/Tron-Hayato/record-edge_20260910_094624.test_left_grab_pcb_from_edge_50eps_cropThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "sam_evt2",
"total_episodes": 51,
"total_frames": 16209,
"total_tasks": 1,
"total_videos": 204,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 30,
"splits": {
"train": "0:51"
},
"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/1g0rrr/test_left_grab_pcb_from_edge_50eps_crop.rithmic-tick-dataedgevane-trainset-1Dataset with wikipedia fitst paragraph and public literature
smolvla-so101-pick-orange-data
SO101 Pick Orange — Teleoperation Dataset
Teleoperated demonstrations of a SO101 robot arm picking three oranges and placing them on a plate in NVIDIA Isaac Sim.
Dataset Details
Property
Value
Robot
SO101 (6-DOF, Feetech STS3215)
Task
Pick 3 oranges → place on plate → return to rest
Environment
NVIDIA Isaac Sim 5.1.0 (kitchen scene)
Teleop Device
SO101 leader arm (ZMQ, 50Hz)
Format
LeRobot v3.0
FPS
30
Episodes
100
Total Frames
60,541… See the full description on the dataset page: https://huggingface.co/datasets/edge-inference/smolvla-so101-pick-orange-data.taccap-g1-wipe-phone-move-case-edge-0731This dataset was created using LeRobot.
Dataset Description
This repository is a public mirror of the original TacVerse dataset. The data, metadata, and videos are mirrored unchanged; this dataset card was regenerated for the XR-Bot1 mirror and adds the original provenance.
Original dataset: TacVerse/taccap-g1-wipe-phone-move-case-edge-0731
Project: LeRobot-Xense: LeRobot with Xense Tactile Robotics Support
License: apache-2.0
Dataset Structure… See the full description on the dataset page: https://huggingface.co/datasets/XR-Bot1/taccap-g1-wipe-phone-move-case-edge-0731.edge-ids-threats
HookProbe Edge IDS Threat Telemetry
Real-world, anonymised threat verdicts from the HookProbe production
edge intrusion-detection system. Unlike synthetic lab datasets
(CICIDS2017, UNSW-NB15, Kitsune) this is what an actual edge sensor
mesh observes on the open internet, labelled by the SENTINEL ensemble
(isolation forest + calibrated naive-Bayes) that ships with HookProbe.
Sensor: Raspberry Pi edge node + NAPSE AI-native flow classifier
Enrichment: RDAP country + ASN lookups… See the full description on the dataset page: https://huggingface.co/datasets/hookprobe/edge-ids-threats.coco_superpixels_edge_wt_region_boundary_30
coco_superpixels_edge_wt_region_boundary_30
Dataset Summary
Dataset
Domain
Task
Node Feat. (dim)
Edge Feat. (dim)
Perf. Metric
COCO-SP
Computer Vision
Node Prediction
Pixel + Coord (14)
Edge Weight (1 or 2)
macro F1
Dataset
# Graphs
# Nodes
μ Nodes
μ Deg.
# Edges
μ Edges
μ Short. Path
μ Diameter
COCO-SP
123,286
58,793,216
476.88
5.65
332,091,902
2,693.67
10.66±0.55
27.39±2.14
Additional Information
Dataset Curators… See the full description on the dataset page: https://huggingface.co/datasets/LRGB/coco_superpixels_edge_wt_region_boundary_30.jamjuri-edge-v4-stage2-datasets
Jamjuri-Edge V4 — Stage 2 Datasets (E1 / E2 / E3)
Cleaned, deduplicated, non-thinking SFT datasets for the Jamjuri-Edge V4 Stage-2 experts.
Series: part of JamjuriEDGE (4B) — collection · series card
✦ English
Overview
Three SFT datasets used to train the Stage-2 experts of
Cheva123/Jamjuri-EDGE-Preview-100,
plus the Stage-1 curriculum mixture (data/stage1/train.parquet) that trained the shared
Stage-1 parent. Every row is pre-rendered with… See the full description on the dataset page: https://huggingface.co/datasets/Cheva123/jamjuri-edge-v4-stage2-datasets.