datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
TrainingData_Stage3
AnchorSR Stage3 · metric-v1.0
直接选择 Small / Large
配置
训练题数
用途
small
1,000,000
先验证答案监督／先验恢复，按新版 Large 联合分布抽样
large
89,801,853
筛选后的完整训练集合，包含 Small 全部样本
from datasets import load_dataset
data = load_dataset('AnchorSR/TrainingData_Stage3', 'small', # 或 large
revision='metric-v1.0', streaming=True)
这是对 scaling-v1.0 的语义筛选与统一任务分类，不是增加新数据源。
Large 从 89,828,269 题保留 89,801,853 题，隔离 26,416 题。
旧标签 scaling-v1.0 / video-v1.0 / large-v1.0… See the full description on the dataset page: https://huggingface.co/datasets/AnchorSR/TrainingData_Stage3.humanoid-robots-training-dataset
Dynamic Intelligence — Humanoid Robot Training Dataset
A first-person (egocentric) video dataset of human hand manipulation, designed for training humanoid robot policies via imitation learning. Each episode captures a person performing an everyday household task — folding clothes, moving dishes, opening doors — filmed from a head-mounted iPhone using its built-in LiDAR and depth sensors.
The dataset pairs each video with frame-level 3D hand tracking and camera pose data, giving… See the full description on the dataset page: https://huggingface.co/datasets/DynamicIntelligence/humanoid-robots-training-dataset.feedback_data_training
Repair replay update — September 15, 2026
The split still contains 161,030 weighted rows, with the same category counts:
Category
Rows
Share
Distinct examples before → after
One-shot
79,970
49.66%
35,197 → 35,197
Regular repairs
60,931
37.84%
40,530 → 48,726
Rollout-derived deep repairs
20,129
12.50%
436 → 1,825
This adds 9,585 distinct checked repair examples while preserving every legacy distinct row and every one-shot row's multiplicity. The new examples… See the full description on the dataset page: https://huggingface.co/datasets/formalmathatepfl/feedback_data_training.Amazon-Fashion-Training-Data-2023
Amazon Reviews 2023
Please also visit amazon-reviews-2023.github.io/ for more details, loading scripts, and preprocessed benchmark files.
[April 7, 2024] We add two useful files:
all_categories.txt: 34 lines (33 categories + "Unknown"), each line contains a category name.
asin2category.json: A mapping between parent_asin (item ID) to its corresponding category name.
This is a large-scale Amazon Reviews dataset, collected in 2023 by McAuley Lab, and it includes rich features… See the full description on the dataset page: https://huggingface.co/datasets/Pandeymp29/Amazon-Fashion-Training-Data-2023.fairness-prm-training-datalilm2-training-dataHIP-training-and-evaluation-data
HIP Training and Evaluation Data
This dataset contains the text data released with Base Models Look Human To AI Detectors for reproducing the Humanization by Iterative Paraphrasing (HIP) training setup and the prefix-based continuation evaluation.
Configs
training
data/train.parquet contains 10,581 supervised HIP training pairs with seven columns:
dataset: upstream dataset family, either raid or mage.
source: selected source domain or subcorpus.
text: original… See the full description on the dataset page: https://huggingface.co/datasets/YixuanEvenXu/HIP-training-and-evaluation-data.act-training-data-picking-up-the-white-cube-v5.0This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so_follower",
"total_episodes": 54,
"total_frames": 46898,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 30,
"splits": {
"train": "0:54"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/leninangelov/act-training-data-picking-up-the-white-cube-v5.0.VLA_Reasoning_Training_Dataset_1200_Trimmed_Start_5_Frame
Spa-Bench fine-tuning demonstrations — motion-trimmed release
This is a non-destructive, motion-trimmed derivative of the
canonical 1,200-episode Spa-Bench dataset.
It removes initial idle prefixes while preserving episode identity, prompt,
action/state alignment, and all five source camera streams at the public head.
Explore episodes in the LeRobot visualizer
Transformation
The baseline is the component-wise median of the first five action frames.
Motion onset… See the full description on the dataset page: https://huggingface.co/datasets/justintiensmith/VLA_Reasoning_Training_Dataset_1200_Trimmed_Start_5_Frame.eti-embedding-training-data-2048-v3
Version note (v3): third generation of the ETI dense training data. Reuses the questions of NorskHelsenett/eti-embedding-training-data-v2 (which trained eti-embeddinggemma-v2), but re-maps every question to its article URL, re-cuts positives at a 2048-token window, re-mines hard negatives with granite + reranker validation (pos_score/neg_score), adds the keyword half, and filters junk anchors. Trained NorskHelsenett/eti-embeddinggemma-v3.
eti-embedding-training-data-2048… See the full description on the dataset page: https://huggingface.co/datasets/NorskHelsenett/eti-embedding-training-data-2048-v3.VLA_Reasoning_Training_Dataset_1200
Spa-Bench fine-tuning demonstrations — full five-camera release
This is the canonical full-length demonstration dataset used by Spa-Bench, a
real-robot benchmark for spatially grounded reasoning in vision-language-action
policies.
Explore episodes in the LeRobot visualizer
Dataset summary
Field
Value
Episodes
1,200
Frames
612,733
Duration at 30 FPS
approximately 5.7 hours
Unique instruction strings
321
Task families
6; 200 demonstrations per… See the full description on the dataset page: https://huggingface.co/datasets/justintiensmith/VLA_Reasoning_Training_Dataset_1200.Training_dataset_by_NAGISA_V4
NAGISA_V4 ply-37 teacher shards, games played to the end
Self-play of attic-gensfen reading the NNUE weights NAGISA_V4
(HalfKA-2304), in the shape the trainers read directly. Every game starts from a
balanced ply-37 position, makes no random moves, and runs until it actually
ends. Identical positions are folded into one row each.
67,108,864 rows — exactly 2^26
16 shards of 4,194,304 rows, 512 row groups each, zstd, 5,208,620,326 B total
Against
Opening_dataset_by_NAGISA_V4… See the full description on the dataset page: https://huggingface.co/datasets/qleap/Training_dataset_by_NAGISA_V4.Training_dataset_qsearched_by_NAGISA_V4
NAGISA_V4 teacher shards, moved to their quiescence leaves
Every record of
Training_dataset_by_NAGISA_V4
walked to the end of its quiescence variation, the deep search's value kept
there, and a policy fitted at the leaf itself.
The parent's positions are as its games reached them, with no quiescence
search — a row can sit in the middle of an exchange, where the evaluation
swings by a piece depending on whose turn it is to recapture. A value fitted on
those learns the swing. This… See the full description on the dataset page: https://huggingface.co/datasets/qleap/Training_dataset_qsearched_by_NAGISA_V4.taxoformer-training-dataact-training-data-picking-up-the-cubeThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so_follower",
"total_episodes": 54,
"total_frames": 46897,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 30,
"splits": {
"train": "0:54"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/leninangelov/act-training-data-picking-up-the-cube.zip-training-hallucination-data-qwen06b-thinking-train-with-valuesVLA_Reasoning_Training_Dataset_1200_2cam
Spa-Bench fine-tuning demonstrations — full two-camera derivative
This is the two-camera projection of the canonical full-length Spa-Bench
demonstration dataset. It retains the middle and wrist views consumed by the
evaluated policies and omits the unused above, left, and right streams.
Explore episodes in the LeRobot visualizer
Dataset summary
Field
Value
Episodes
1,200
Frames
612,733
Unique instruction strings
321
Frame rate
30 FPS
Camera… See the full description on the dataset page: https://huggingface.co/datasets/justintiensmith/VLA_Reasoning_Training_Dataset_1200_2cam.credit-scoring-training-datasetThe training dataset includes all addresses that had undertaken at least one borrow transaction on Aave v2 Ethereum or Compound v2 Ethereum any time between 7 May 2019 and 31 August 2023, inclusive (called the observation window).
Data Structure & Shape
There are almost 0.5 million observations with each representing a single borrow event. Therefore, all feature values are calculated as at the timestamp of a borrow event and represent the cumulative positions just before the borrow event's… See the full description on the dataset page: https://huggingface.co/datasets/spectrallabs/credit-scoring-training-dataset.open-synth-training-dataTrainingDatasetfeedback_data_training_chat_templatestt-training-data
Dataset Statistics
Configuration: default
Split: train
Total Rows: 1,362,015
dept
Type: categorical
Data Type: object
Unique Values: 8
Value Distribution:
Value
Count
Percentage
STT_TT
446,495
32.78%
STT_NS
236,407
17.36%
STT_AB
170,922
12.55%
STT_CS
146,811
10.78%
STT_MV
110,080
8.08%
STT_NW
94,703
6.95%
STT_HS
84,797
6.23%
STT_PC
71,800
5.27%
grade
Type: numerical
Data Type: int64
Sum: 3,963,451.00… See the full description on the dataset page: https://huggingface.co/datasets/openpecha/stt-training-data.t2i-nla-multidomain-1m-training-data-public
T2I-NLA Multidomain 1M Training Data
Public backup of final T2I-NLA reader training data.
Balanced multidomain 1M training data for general FLUX AR/AV readers.
This repository is intended to make final-reader retraining possible after the
original server is no longer available.
See manifest.json for the original local path, size, and associated reader models.
humanoid-robots-training-dataset
Dynamic Intelligence — Humanoid Robot Training Dataset
A first-person (egocentric) video dataset of human hand manipulation, designed for training humanoid robot policies via imitation learning. Each episode captures a person performing an everyday household task — folding clothes, moving dishes, opening doors — filmed from a head-mounted iPhone using its built-in LiDAR and depth sensors.
The dataset pairs each video with frame-level 3D hand tracking and camera pose data, giving… See the full description on the dataset page: https://huggingface.co/datasets/introvoyz043/humanoid-robots-training-dataset.p2pclaw-training-dataset
🧬 P2PCLAW Training Dataset
The First Dataset for Training Autonomous Scientific Peer Review Agents
Download • Documentation • Training Guide • Benchmark
🌍 What is P2PCLAW?
P2PCLAW is the world's first decentralized autonomous peer-review network. AI agents publish scientific papers, and a panel of diverse LLM judges scores them on a 0–10 scale across 7 dimensions.
This dataset contains 751 papers evaluated by 7–12 LLM judges simultaneously… See the full description on the dataset page: https://huggingface.co/datasets/Agnuxo/p2pclaw-training-dataset.training_datasetThis 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/sagnikroy75/training_dataset.scoutgpt-training-data
ScoutGPT Training Data — Player Action Sequences
Per-player match-level action sequences unified across StatsBomb Open Data and Wyscout open data. Each row is one player-match's ordered SPADL action sequence with contextual tokens (competition, season, score state, half, opponent), serialized as the token stream that the ScoutGPT transformer consumes during training and at inference.
Part of the (Right! Luxury!) Lakehouse soccer analytics platform.
Quick Start… See the full description on the dataset page: https://huggingface.co/datasets/luxury-lakehouse/scoutgpt-training-data.training_datasetThis 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/hspanjeta/training_dataset.deeplm-training-data🚧🚧UNDER CONSTRUCTION🚧🚧
training_datasetThis 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/Asparagus7386/training_dataset.