datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
pai-interview-a1-forklift-pallet-transport-vizThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "isaacsim_forkliftC",
"total_episodes": 2,
"total_frames": 5497,
"total_tasks": 2,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 10,
"splits": {
"train": "0:2"
},
"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/geonmin-kim/pai-interview-a1-forklift-pallet-transport-viz.Palladium-1M-Preview
💎 Palladium-1M: High-Density Information for Efficient LLM Training
Palladium-1M is a curated dataset of ~1 million high-entropy, high-sophistication documents (13.5GB), mined from the open web using a novel Physics-Based Filtration System.
Unlike standard filters that rely on heuristics or keywords, the Palladium Refinery uses Information Theory (ZSTD Compression Ratios) and Linguistic Density to mathematically distinguish "Signal" from "Noise."
The result is a dataset that trains… See the full description on the dataset page: https://huggingface.co/datasets/PalladiumData/Palladium-1M-Preview.africa-synth-cancer-palliative-care-africa-all
Palliative Care Access - Africa | Africa (Electric Sheep Africa metadata inventory)
Size category: 10K<n<100K - Formats: not declared - Sector: health - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Health datasets… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-cancer-palliative-care-africa-all.palliative-care-pain-management
Palliative Care & Pain Management (Opioid Access, WHO Ladder, Quality of Life) | Africa (World Health Organization)
Size category: 10K<n<100K - Formats: csv - Sector: health - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/palliative-care-pain-management.pallasbench-robust-gpu-a100
PallasBench: Robust Pallas GPU Kernel Benchmark (A100)
39/45 kernels passing on NVIDIA A100 80GB -- the first GPU-focused evaluation of JAX Pallas kernels.
What is this?
PallasBench is a suite of 45 JAX Pallas kernels across 3 difficulty levels. The original kernels were designed for TPU and failed on GPU because Pallas compiles to Triton on NVIDIA hardware, which has strict block size limits that TPU's Mosaic compiler does not.
We fixed all 45 kernels for GPU… See the full description on the dataset page: https://huggingface.co/datasets/EvanOLeary/pallasbench-robust-gpu-a100.pallasbench-unifiedsuperkart-datasetflower_smellspallasbench-archiveNLSmellglp1-telehealth-rules-us
GLP-1 Telehealth Rules by U.S. State
Which U.S. jurisdictions (50 states + Washington, D.C.) require a live video
visit to start GLP-1 treatment by telehealth — plus each jurisdiction's medical
board, Medicaid GLP-1 coverage status, and nurse practitioner
prescriptive-authority classification (full/reduced/restricted) verified
against state nurse practice acts with statute citations.
Canonical, always-current source: https://www.pallashealth.co/glp-1/telehealth-rules
Live CSV:… See the full description on the dataset page: https://huggingface.co/datasets/pallas-health/glp1-telehealth-rules-us.restaurantNLPamazon_reviewsLLCP2023tourism-dataset-traintourism-dataset-testbox_palletizing_teleoperation_1_10_20260923_182129This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"action": {
"dtype": "float32",
"names": [
"waist_0.pos",
"waist_1.pos",
"waist_2.pos",
"left_leg_0.pos",
"left_leg_1.pos",
"left_leg_2.pos",
"left_leg_3.pos",
"left_leg_4.pos"… See the full description on the dataset page: https://huggingface.co/datasets/Inhachoi/box_palletizing_teleoperation_1_10_20260923_182129.