datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
PAMIPPAM_data
PAM19
PAM19 is a real-world Franka Panda tactile-manipulation dataset containing
1,904 trajectories across 19 tasks. Demonstrations were collected in joint
space with two RGB cameras and two Xense vision-based tactile sensors, then
converted to FTP-1-compatible Zarr format.
The dataset follows the
Open-X-Tactile / FTP-1 data convention.
Dataset summary
Robot: Franka Panda with a parallel gripper
Tactile sensor: Xense, two gripper-side image streams
RGB streams:… See the full description on the dataset page: https://huggingface.co/datasets/cloudfan/PAM_data.PAMELA
PAM∃LA
Personalizing Text-to-Image Generation to Individual Taste
Anne-Sofie Maerten1,2,
Juliane Verwiebe2,
Shyamgopal Karthik2,
Ameya Prabhu2,
Johan Wagemans1,
Matthias Bethge2
1Tübingen AI Center, University of Tübingen
2Department of Brain and Cognition, KU Leuven
PAM∃LA is a dataset of AI-generated images rated by human participants for aesthetic quality. It pairs each rating with rich participant demographics… See the full description on the dataset page: https://huggingface.co/datasets/bethgelab/PAMELA.TDC_pampa_ncats
TDC PAMPA NCATS
PAMPA NCATS dataset [1], part of TDC [2] benchmark. It is intended to be used through
scikit-fingerprints library.
NCATS subset of PAMPA dataset.
PAMPA (parallel artificial membrane permeability assay) is an assay to evaluate drug permeability across the cellular membrane. The task models only the passive membrane diffusion. This is “NCATS” subset of the dataset created at National Center for Advancing Translational Sciences (NCATS).
This dataset is a part of… See the full description on the dataset page: https://huggingface.co/datasets/scikit-fingerprints/TDC_pampa_ncats.coconut-gsm8k-latents
COCONUT GSM8K latent caches (Part II)
Cached artifacts for Part II of pau_amargantialvarez_408221.ipynb — the interpretability analysis
of four latent-reasoning models on the GSM8K test split (N=1319). CPU-only: the notebook reads
these dumps; a RECOMPUTE toggle re-derives them on GPU from the checkpoints.
Current schema (per recompute in latent_lib.py): each latents_<tag>.pt is a dict with
acc, n, example_idx, report_name, and the per-slot tensors — latent_768 (parent) or… See the full description on the dataset page: https://huggingface.co/datasets/pamargantal/coconut-gsm8k-latents.wbes-faceembedding-repo-snapshot
WBES-FaceEmbedding Repository Snapshot
This dataset repository stores a compressed workspace snapshot for the WBES-FaceEmbedding NeurIPS 2026 submission repository.
Snapshot Contents
The archive is intended to preserve the local research codebase state, including:
repository documentation and helper scripts
face_embedding/ modeling, robustness, checkpoint, and evaluation artifacts
faceBench/ and faceBench/latentVSpipeline/
datasets/FaceVerse/ processing, evaluation, and… See the full description on the dataset page: https://huggingface.co/datasets/Pampaj/wbes-faceembedding-repo-snapshot.PAMAP2Part of MONSTER: https://arxiv.org/abs/2502.15122.
PAMAP2
Category
HAR
Num. Examples
38,856
Num. Channels
52
Length
100
Sampling Freq.
100 Hz
Num. Classes
12
License
Other
Citations
[1]
PAMAP2 is a collection of data obtained from three Inertial Measurement Units (IMUs) placed on the wrist of the dominant arm, chest, and ankle, as well as 1 ECG heart rate [1]. The data was recorded at a frequency of 100Hz. The dataset includes annotated information about human… See the full description on the dataset page: https://huggingface.co/datasets/monster-monash/PAMAP2.PAMAP2
PAMAP2
The PAMAP2 Physical Activity Monitoring dataset contains data of 18 different physical activities, performed by 9 subjects wearing 3 inertial measurement units and a heart rate monitor.
A. Reiss and D. Stricker, "Introducing a New Benchmarked Dataset for Activity Monitoring," 2012 16th International Symposium on Wearable Computers, Newcastle, UK, 2012, pp. 108-109, doi: 10.1109/ISWC.2012.13.
Dataset Information
The PAMAP2 Physical Activity Monitoring dataset… See the full description on the dataset page: https://huggingface.co/datasets/rnicrosoft/PAMAP2.pamela
PAM∃LA
Personalizing Text-to-Image Generation to Individual Taste
Anonymous submission — author and affiliation details withheld during review.
PAM∃LA is a dataset of AI-generated images rated by human participants for aesthetic quality, built specifically for personalization research. It pairs each rating with rich participant demographics and image metadata, enabling research on personalized aesthetic prediction, demographic variation in visual preference, and reward modelling for… See the full description on the dataset page: https://huggingface.co/datasets/pamela-dataset/pamela.TDC_pampa_approved_drugsPAM-data
Perceive Anything: Recognize, Explain, Caption, and Segment Anything in Images and Videos
Perceive Anything Model (PAM) is a conceptually simple and efficient framework for comprehensive region-level visual understanding in images and videos. Our approach extends SAM 2 by integrating Large Language Models (LLMs), enabling simultaneous object segmentation with the generation of diverse, region-specific semantic outputs, including categories, label definition, functional explanations… See the full description on the dataset page: https://huggingface.co/datasets/Perceive-Anything/PAM-data.upper-waiakea-PAM
Dataset Card for Upper Waiākea Forest Reserve Passive Recordings
Dataset Details
Dataset Description
This is a dataset containing unlabelled, unprocessed passive acoustic recordings of Hawaiian birds in the Upper Waiākea Forst Reserve in Hawaii. This dataset is intended for use in unsupervised audio analysis methods, classification using existing models, and other machine learning and ecology research purposes.
Supported Tasks and… See the full description on the dataset page: https://huggingface.co/datasets/imageomics/upper-waiakea-PAM.pa-minimal-green-team-SFT-500m
pa-minimal-green-team-SFT-500m
The PA green-team minimal 500M SFT mix — math + science + light agentic, short-reasoning-first.
Two training configs (same 216,668 documents, same order):
config
tokens
what
math_sci_agentic_500m
500.0M
reasoning traces intact (think)
math_sci_agentic_500m_nothink
131.8M
every trace replaced by a literal empty <think></think> (no-think)
Composition: 37.7% math_reasoning · 36.3% science_mcq · 16.7% science_research · 9.4%… See the full description on the dataset page: https://huggingface.co/datasets/geodesic-research/pa-minimal-green-team-SFT-500m.pampa_ncats-multimodalswe-gym-trainganymedegem-analysis-pamap2
gem-analysis-pamap2
PAMAP2 physical activity monitoring dataset
数据集信息
来源路径: datasets/pamap2
数据大小: 1.6 GB
用途: 健身动作识别模型训练
使用方法
from huggingface_hub import snapshot_download
# 下载数据集
snapshot_download(
repo_id="yonful/gem-analysis-pamap2",
repo_type="dataset",
local_dir="./datasets/pamap2"
)
或使用项目中的下载脚本:
python scripts/prepare_data.py --dataset pamap2
许可证
请参考原始数据源的许可证要求。
swe-gym-test-getmotoswe-gym-testpamap2_physical_activity_monitoringolivers-mtor-atlas
Oliver's mTOR Atlas
The mTOR pathway, mapped by what the evidence can actually carry. This dataset is the curated corpus behind mtor-atlas.org: 411 hand-selected studies on mTOR (mechanistic target of rapamycin) signalling, each labelled by the kind of study behind it, and a list of 149 pathway entities (genes and proteins, complexes, drugs, interventions, biological processes, diseases, outcomes, organelles, nutrients and conditions) that the studies refer to.
Homepage:… See the full description on the dataset page: https://huggingface.co/datasets/pampalini1/olivers-mtor-atlas.pamiat_merkuria_azurlane
Dataset of pamiat_merkuria/パーミャチ・メルクーリヤ/水星纪念 (Azur Lane)
This is the dataset of pamiat_merkuria/パーミャチ・メルクーリヤ/水星纪念 (Azur Lane), containing 349 images and their tags.
The core tags of this character are long_hair, breasts, large_breasts, black_hair, purple_eyes, bangs, hat, one_side_up, white_headwear, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).… See the full description on the dataset page: https://huggingface.co/datasets/CyberHarem/pamiat_merkuria_azurlane.Pamir_Visual-Inertial_Data
Pamir Visual/Inertial Dataset
This dataset contains visual inertial data for three experiments at the Pamir shipwreck, Barbados.
Three dives were performed at the Pamir shipwreck with durations of 55 (2024), 51 and 51 (2025) minutes respectively, while data were recorded for 39, 44, and 45 minutes respectively. In the first dive the cameras were attached to a
sensor rig. In the second and third dives two calibration targets (4-by-2 and 5-by-4) were deployed in two different… See the full description on the dataset page: https://huggingface.co/datasets/afrl-uw/Pamir_Visual-Inertial_Data.ena24PAMAP2_CLEANEDredred-gemma-4-E2B-it-lora-summariespampa_ncats
Dataset Details
Dataset Description
PAMPA (parallel artificial membrane permeability assay) is a commonly
employed assay to evaluate drug permeability across the cellular membrane.
PAMPA is a non-cell-based, low-cost and high-throughput alternative to cellular models.
Although PAMPA does not model active and efflux transporters, it still provides permeability values
that are useful for absorption prediction because the majority of drugs are absorbed
by passive diffusion… See the full description on the dataset page: https://huggingface.co/datasets/jablonkagroup/pampa_ncats.ovenbird-individual-songs-pam-datasetcoconut-fsq-ablation
COCONUT-FSQ bottleneck ablation — cached artifacts
Companion caches for Part I of pau_amargantialvarez_408221.ipynb (Pau Amargant Alvarez, MNLP).
FSQ-COCONUT fine-tuned from plain COCONUT (gsm-coconut/checkpoint_25), varying only fsq_levels.
Each run taken at its best-validation checkpoint and evaluated on the GSM8K test split (N=1319),
through the same harness as the interpretability part.
config
fsq_levels
K
d
best val
test acc
active codes
eff. ppl
collapsed dims… See the full description on the dataset page: https://huggingface.co/datasets/pamargantal/coconut-fsq-ablation.pama