datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
nara_revolutionary_war_pension_files_PDFs
Dataset Card for American Revolutionary War Pension Files - File-Level
Dataset Summary
A dataset derived from the National Archives and Records Administration (NARA) series Case Files of Pension and Bounty-Land Warrant Applications Based on American Revolutionary War Service (NARA Catalog Series, NAID 300022). This dataset provides a file-level representation of Revolutionary War pension records, aggregating individual page records into complete pension files… See the full description on the dataset page: https://huggingface.co/datasets/RevolutionCrossroads/nara_revolutionary_war_pension_files_PDFs.terminal-bench-2
Terminal-Bench-2.0 Beta
Welcome to Terminal-Bench-2.0! If you’re reading this you’re a member of the Terminal-Bench community that we’ve selected to get a sneak peek at the latest version of the benchmark.
Getting Started
First, clone Harbor (formerly “Sandboxes”):
git clone https://github.com/laude-institute/harbor.git
From inside the Harbor directory run:
uv sync
This will install Harbor, our new package for running agent evals.
You should now be able to run TB 2.0!… See the full description on the dataset page: https://huggingface.co/datasets/penfever/terminal-bench-2.PenaldoCR7youcook2Due to requests and inaccessibility of online videos, we are sharing the raw video files. By downloading these files, you are agreeing to use them for non-commercial, research purposes only.
histogpt-datasetgdrive-data-backuplibero-pi3x-targets-224
LIBERO Pi3X Targets (224×224)
This dataset contains precomputed Pi3X geometry targets for two LIBERO camera streams.
The source images and camera intrinsics were resized from 256 × 256 to 224 × 224 and processed with yyfz233/Pi3X. The targets are stored per episode and per camera.
Dataset contents
Item
Value
Episodes
1,768
Source frames
286,537
Cameras
agent, wrist
Resolution
224 × 224
NPZ files
3,536
Size
230.0 GB (214.2 GiB)
Dtype
float16… See the full description on the dataset page: https://huggingface.co/datasets/pengyue-polaron/libero-pi3x-targets-224.CrossPannyush-galaxea-a1-lingbot-va-real-world-evaluations
LingBot-VA on Galaxea A1 — Real-World Evaluations
Fruit-placement rollouts and open-loop diagnostics of object grounding,
layout generalization, and predicted robot motion.
Fruit step-1000: lemon-to-plate rollout in the Official layout.
Evidence
Scale
Real closed-loop rollouts
61 archived; 60 scored
Matched base-model controls
9 predictions
Post-trained diagnostics
48 full-horizon predictions; 1,211 rolling futures
Controlled OOD studies
558 predictions… See the full description on the dataset page: https://huggingface.co/datasets/pengyue-polaron/nyush-galaxea-a1-lingbot-va-real-world-evaluations.galaxy-ssd-pengchx3-backupTTS_ArenaTTS Arena's DB is SQLlite DB file. The above is just a summary query that should be useful for TTS developers to evaluate faults of their model.
Why no audio samples?
Unsafe. Cannot constantly oversee the output of uncontrolled HuggingFace Spaces. While it could be safeguarded by using an ASR model before uploading, something unwanted may still slip through.
Useful queries for TTS developers and evaluators
All votes mentioning specified TTS model:… See the full description on the dataset page: https://huggingface.co/datasets/Pendrokar/TTS_Arena.Cobot_Magic_take_out_a_pen_from_the_pen_holder
Cobot_Magic_take_out_a_pen_from_the_pen_holder
📋 Overview
This dataset uses an extended format based on LeRobot and is fully compatible with LeRobot.
Robot Type: agilex_cobot_decoupled_magic
| Codebase Version: v2.1
End-Effector Type: two_finger_gripper
🏠 Scene Types
This dataset covers the following scene types:
office
home
🤖 Atomic Actions
This dataset includes the following atomic actions:
grasp
pick
place
📊… See the full description on the dataset page: https://huggingface.co/datasets/RoboCOIN/Cobot_Magic_take_out_a_pen_from_the_pen_holder.aloha_pen_uncap
Dataset Card for aloha_pen_uncap
This dataset is a FiftyOne conversion in LeRobot format of the aloha_pen_uncap_diverse subset of BiPlay.
The aloha_pen_uncap_diverse subset is a task-specific segment of BiPlay focusing on the long-horizon, dexterous bimanual task of un-capping a pen under diverse conditions. It contains episodes where the robot is required to grasp a pen and successfully remove its cap—an action requiring coordination and dexterity—across a wide range of object… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/aloha_pen_uncap.pending-medicare-provider-enrollment-data
Pending Medicare Provider Enrollment Data
This is a dated, source-receipted sample of behavioral-health NPIs newly present in CMS's pending first-time Medicare enrollment files on 2026-07-13, compared with the immediately prior 2026-07-09 publication.
Pending does not mean approved. A row indicates that a first-time Medicare enrollment application appeared in a CMS pending file. It does not prove enrollment, credentialing, licensure, a new practice, service availability… See the full description on the dataset page: https://huggingface.co/datasets/unitedideas/pending-medicare-provider-enrollment-data.stable-diffusion-webui
Stable Diffusion web UI
A browser interface based on Gradio library for Stable Diffusion.
Features
Detailed feature showcase with images:
Original txt2img and img2img modes
One click install and run script (but you still must install python and git)
Outpainting
Inpainting
Color Sketch
Prompt Matrix
Stable Diffusion Upscale
Attention, specify parts of text that the model should pay more attention to
a man in a ((tuxedo)) - will pay more attention to tuxedo
a man in a… See the full description on the dataset page: https://huggingface.co/datasets/PennyJX/stable-diffusion-webui.RealBench
RealBench
Overview
RealBench is a benchmark for complex IP design tasks in real scenarios. It has the following features
More complex tasks
System-level and module-level tasks
Multi-modal data
Syntax, function, and formal correctness verification
Setup Linux Environment
Use conda to set up this environment
configure conda environment
conda env create -f conda_env.yml
Check tool version
conda activate realbench
python… See the full description on the dataset page: https://huggingface.co/datasets/Pengwei-Jin/RealBench.AI2_Alphabot_2_place_pen
AI2_Alphabot_2_place_pen
Dataset Description
This dataset uses an extended format based on LeRobot and is fully compatible with LeRobot.
Task Preview
View Video Directly
Overview
Total Episodes: 527
Total Frames: 666384
FPS: 30
Dataset Size: 13.18 GB
Robot Name: AI2_Alphabot_2
End-Effector Type: two_finger_end_effector
Teleoperation Type: vr_controller
Sensors: cam_front_chest_rgb,
cam_front_head_rgb,
cam_left_wrist_rgb… See the full description on the dataset page: https://huggingface.co/datasets/RoboCOIN/AI2_Alphabot_2_place_pen.PENCILAI2_Alphabot_2_organize_pencil_holder
AI2_Alphabot_2_organize_pencil_holder
Dataset Description
This dataset uses an extended format based on LeRobot and is fully compatible with LeRobot.
Task Preview
View Video Directly
Overview
Total Episodes: 392
Total Frames: 323948
FPS: 30
Dataset Size: 17.18 GB
Robot Name: AI2_Alphabot_2
End-Effector Type: two_finger_end_effector
Teleoperation Type: vr_controller
Sensors: cam_front_chest_rgb,
cam_front_head_rgb… See the full description on the dataset page: https://huggingface.co/datasets/RoboCOIN/AI2_Alphabot_2_organize_pencil_holder.G1_Dex1_Pack_PencilBoxThis dataset was created using LeRobot.
Due to the inability to precisely describe spatial positions, adjust the scene to closely match the first frame of the dataset after installing the hardware as specified in Part 5 of AVP Teleoperation Documentation.
Data collection is not completed in a single session, and variations between data entries exist. Ensure these variations are accounted for during model training.
Dataset Structure
meta/info.json:
{
"codebase_version":… See the full description on the dataset page: https://huggingface.co/datasets/unitreerobotics/G1_Dex1_Pack_PencilBox.S3E S3E: A Mulit-Robot Multimodal Dataset for Collaborative SLAM
[!TIP]
This is a project website of S3E dataset.
Feel free to open a
disccussion.
KNOWN ISSUES
[!IMPORTANT]
For experimental sequences in the laboratory, we capture only the start and end points due to constraints in Vicon system availability. Evaluation of these sequences is subsequently performed using only these two reference points.
nara_revolutionary_war_pension_files
Dataset Card for American Revolutionary War Pension Files
Dataset Summary
A dataset derived from the Case Files of Pension and Bounty-Land Warrant Applications Based on American Revolutionary War Service, ca. 1800–ca. 1912 (NARA Catalog Series, NAID 300022). This dataset includes page-level records with digitized images, original extracted text (by Family Search), AI-generated OCR, and human-created transcriptions where available. It offers a unique window into… See the full description on the dataset page: https://huggingface.co/datasets/RevolutionCrossroads/nara_revolutionary_war_pension_files.PENGWIN_Task2
PENGWIN Task 2: Pelvic Fragment Segmentation on Synthetic X-ray Images
Mirror of the training split of Task 2 of the MICCAI 2024 PENGWIN challenge
(https://pengwin.grand-challenge.org/), from the official Zenodo record
10913196 (train.zip, md5 9c90215dae54d8f494a85cfc7b19bc96).
These are SYNTHETIC X-rays, not real radiographs: DeepDRR renders of the 100 PENGWIN
Task 1 training CTs simulating intraoperative C-arm fluoroscopy, 500 random poses per CT
= 50,000 image/mask pairs.… See the full description on the dataset page: https://huggingface.co/datasets/MedOtter/PENGWIN_Task2.ablation_exploration_in_rl
Reinforcement Learning Improves Agentic Software Engineering
An ablation study of reinforcement-learning (RL) fine-tuning for agentic software-engineering (SWE) models. Starting from an 8B SFT model, we fine-tune with RL across ~20 configurations — varying the objective, loss normalization, sampling, and training dataset — and evaluate each on agentic SWE benchmarks.
Result
RL reliably and substantially improves agentic SWE performance, and the improvement is… See the full description on the dataset page: https://huggingface.co/datasets/penfever/ablation_exploration_in_rl.Knowledge_distilled_dataset_by_NAGI将棋AI用の知識蒸留済みのデータセットを公開します。およそ80億局面あります。 nodchip氏が公開しているtanuki-.nnue-pytorch-2024-07-30.1をhaoでqsearchシャッフルしたのち自作のNAGI(非公開)で評価値を書き換えました。Eval_Coef=600でDLモデルのvalueと評価値を変換しています。 データにバグがあるかもしれませんが、品質保証はしません。
https://huggingface.co/datasets/nodchip/tanuki-.nnue-pytorch-2024-07-30.1
ffw_bg2_rev4_test_pen_in_cup_01penumbra-dataset-public
Private encrypted archive
This repository is used only as encrypted blob storage. The contents are
AES-256 encrypted and are not a usable public dataset. No license to use
the underlying data is granted.
JANuS_datasetThis repository hosts the JANuS (Joint Annotations and Names) dataset introduced in the 2023 paper Distributionally Robust Classification on a Data Budget.
As of this writing, ours is the only public dataset which is both fully annotated with ground-truth labels and fully captioned with web-scraped captions.
It is designed to be used for controlled experiments with vision-language models.
What is in JANuS?
JANuS provides metadata and image links for four new training datasets; all… See the full description on the dataset page: https://huggingface.co/datasets/penfever/JANuS_dataset.flawed-summ-evalsvedio-to-skill