datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
separate-robots-sweep-cubesThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "ur5-panda",
"total_episodes": 360,
"total_frames": 109008,
"total_tasks": 1,
"total_videos": 0,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 10,
"splits": {
"train": "0:360"
},
"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/rdoshi21/separate-robots-sweep-cubes.EgoLoc-Separation-GRPO
EgoLoc Separation GRPO Dataset
This is a self-contained 3x3 image-grid dataset for GRPO training on exact
separation/end localization. The numbered cells are chronological and use 1-based
indices.
This dataset is used to improve a VLM's accuracy for the EgoLoc pipeline.
This dataset IS NOT shuffled. When undergoing GRPO, recommend shuffling the dataset.
3x3 grid dataset for VLM tuning on separation frame identification.
Splits
Training rows: 1127
Validation rows:… See the full description on the dataset page: https://huggingface.co/datasets/yuchenxie/EgoLoc-Separation-GRPO.sept15_lerobot_bottle_taskThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "",
"total_episodes": 124,
"total_frames": 70555,
"total_tasks": 2,
"total_videos": 0,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 50.0,
"splits": {
"train": "0:124"
},
"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/gauravpradeep/sept15_lerobot_bottle_task.xlerobot-left-pick-cup-sep2-20260902-1819MMR-Life
MMR-Life (Multimodal Multi-image Reasoning Benchmark under Real-life Scenarios)
Dataset Description
We introduce MMR-Life, a benchmark curated to evaluate the ability of MLLMs to perform diverse types of reasoning in everyday situations. MMR-Life consists of 2,646 questions based on 19,238 images, covering 7 reasoning types (i.e., abductive, analogical, causal, deductive, inductive, spatial, and temporal) and 21 tasks. Each task is based on a set of multi-images sourced… See the full description on the dataset page: https://huggingface.co/datasets/Septzzz/MMR-Life.EgoLoc-Separation-Detection
Separation Frame SFT Dataset
This dataset is used to improve a VLM's accuracy for the EgoLoc pipeline.
This dataset IS NOT shuffled. When undergoing SFT, recommend shuffling the dataset.
3x3 grid dataset for VLM fine-tuning on separation frame identification.
Training videos: 175
Eval videos: 20 (10 DeskTIL + 10 EgoPAT3D)
Grid variants: 9 per video (GT frame at each cell position)
Training rows: 1127
Eval rows: 112
Skipped training rows (edge cases): 448
Skipped eval rows (edge… See the full description on the dataset page: https://huggingface.co/datasets/yuchenxie/EgoLoc-Separation-Detection.xlerobot-left-pick-cup-sep3-20260903-2015sephora_products
🧴 Sephora Products Dataset — EDA & Insights
Sephora is a global beauty product store that sales products from thousands of brands.
The dataset I will present in the project includes 8,494 records represent a different product (some from the same company) and 27 features
such as product name, price, size, rating, category.
This project analyzes Sephora’s product dataset describing product attributes, pricing and popularity indicators.
The goal of the analysis is to explore whitch… See the full description on the dataset page: https://huggingface.co/datasets/MayaKitzis/sephora_products.street2shop_separate_imagesSepctral_filesxlerobot-left-pick-cup-sep3-20260903-2054neonatal-sepsis-care
Neonatal Sepsis & Newborn Care (Blood Culture, Pathogens, KMC, Outcomes) | Africa (Electric Sheep Africa metadata inventory)
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… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/neonatal-sepsis-care.OOD_8_SEPmirror-mouse-separate
Mirror Mouse — Lightning Pose Multi-View Dataset
Multi-camera pose estimation dataset for mouse locomotion keypoints, packaged for use with Lightning Pose.
Dataset Description
Head-fixed mice run on a circular treadmill while avoiding a moving obstacle (Warren et al., eLife 2021). The treadmill has a transparent floor and a mirror mounted inside at 45°, allowing a single camera to capture two roughly orthogonal views — a side view and a bottom view via the mirror… See the full description on the dataset page: https://huggingface.co/datasets/paninski-lab/mirror-mouse-separate.positive-outcomes-ymyl-entity-separation
Positive Outcomes Entity-Clarity Case Study
This dataset documents a public entity-clarity workflow for a local clinical psychology practice where public search and directory signals blended a solo practitioner practice with colocated but separate providers.
Public record: Zenodo DOI 10.5281/zenodo.21171669
Public record creators: Richard Amir Nasser; Harvey L. Gayer, Ph.D.
Repository: https://github.com/RichNass87/positive-outcomes-doctor-ymyl-blueprint
Research app:… See the full description on the dataset page: https://huggingface.co/datasets/InspectorRoofing/positive-outcomes-ymyl-entity-separation.bottle_square_sept7_lerobotThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "",
"total_episodes": 102,
"total_frames": 30816,
"total_tasks": 1,
"total_videos": 0,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 50.0,
"splits": {
"train": "0:102"
},
"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/gauravpradeep/bottle_square_sept7_lerobot.Collected_Separatedermnet-sepnil-qna-style-fixedntnudermnet-sepnil-qna-styleShimmerSignal-Separatedcontrolnet_canny_segmented_tomato_Tomato_Septoria_leaf_spotcommunes-ayant-remporte-plusieurs-labels-septembre-2023
Communes ayant remporté plusieurs labels - Septembre 2023
Source
Source officielle : https://www.data.gouv.fr/datasets/communes-ayant-remporte-plusieurs-labels-septembre-2023
Identifiant du jeu de données data.gouv.fr : 64f8728b8f37829f9302ce57
Slug data.gouv.fr : communes-ayant-remporte-plusieurs-labels-septembre-2023
Licence indiquée dans les métadonnées data.gouv.fr : lov2
Structure Hugging Face
Un jeu de données data.gouv.fr = un dépôt… See the full description on the dataset page: https://huggingface.co/datasets/Data-Gouv-ML/communes-ayant-remporte-plusieurs-labels-septembre-2023.september1dermnet-sepnilEXSCLAIM-figure-separator
Figure Separation Training Data For EXSCLAIM
Data Fields
One record refers to one figure's information from the paper.
Journal: String. The journal that this article was taken from (i.e., arXiv, Nature)
ID: String. The ID of the article that this figure comes from, as well as it's figure number.
URL: String. The ID to the article.
Image: PIL.Image.Image. A PIL instance of the image.
Info:
Master Image: List[].
Subfigure Label: List[].
Scale Bar Label: List[].… See the full description on the dataset page: https://huggingface.co/datasets/lwashington3/EXSCLAIM-figure-separator.livestock-image-datasettwitter-Lucas777o-2026.01.15-2011713051658203452-SEpXmbSSOZyb4vsG-part1sep20_smoketest