datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SQuADDS_Layouts
SQuADDS Layouts - versioned GDS artifacts for superconducting quantum hardware
SQuADDS Layouts is the geometry-artifact companion to
SQuADDS_DB, the
Superconducting Qubit And Device Design and Simulation Database. It provides
checksum-verified GDS files, stable geometry identities, and machine-readable
geometry metadata so a simulation result can be traced to the exact layout
that produced it.
Homepage: https://lfl-lab.github.io/SQuADDS/
Repository:… See the full description on the dataset page: https://huggingface.co/datasets/SQuADDS/SQuADDS_Layouts.room-layout-planning-curated-v1
Room Layout Planning — curated pilot v1
39 个逐条检查并编写需求的房间布局任务，供实验流程验证与人工抽查。所有最终设计需求均为 AI 编写；没有人工标注或人工复核声明。
Split
条数
独立房屋
几何来源
train
26
26
InstructScene / 3D-FRONT
val_seen
7
7
InstructScene / 3D-FRONT
val_unseen
6
5
M3DLayout / Matterport3D
输入：英文使用需求 + 可用地板多边形 + 4–10 件家具及固定宽深尺寸。输出：所有家具的二维位置与旋转角度。家具清单和尺寸不可修改。参考摆放已通过几何检查，但没有被认证为满足全部语言偏好的标准答案。
下载后打开 review.html 可以逐条浏览需求、尺寸、空房轮廓、参考图和修订理由。原文与 46 条逐条审核记录见 individual_reviews.jsonl，其中 39 条保留、7 条排除。此次规模适合跑通… See the full description on the dataset page: https://huggingface.co/datasets/yfan1997/room-layout-planning-curated-v1.SQuADDS_Layout_Embeddings
SQuADDS Layout Embeddings
Versioned layout representations for the 24,106 GDS artifacts in
SQuADDS/SQuADDS_Layouts.
Static embedding model v0
static-embedding-v0 implements the original SQuADDS proof-of-concept model:
v0 = parameter_sum + geometric_moments + flattened_shape_bitmap
Each unit-normalized vector has 9,227 dimensions:
Block
Dimensions
Contents
Parameter sum
1
Permutation- and parameter-count-invariant sum of numerical design options… See the full description on the dataset page: https://huggingface.co/datasets/SQuADDS/SQuADDS_Layout_Embeddings.DocVQA_layoutLM
Dataset Card for "DocVQA_layoutLM"
More Information needed
persian-ocr-community-dataset-layout
Persian OCR Community Layout Annotations
Resumable layout annotations for the page images in
Reza2kn/persian-ocr-community-dataset.
Each row points to an exact source dataset revision, Parquet shard, blob, and row. It includes the
page identifier, page dimensions, handwriting flag, and structured layout boxes produced by
datalab-to/surya_layout2 at confidence threshold
0.4.
The boxes field contains label, confidence, raster-order position, and pixel coordinates
x0, y0, x1, y1.… See the full description on the dataset page: https://huggingface.co/datasets/Reza2kn/persian-ocr-community-dataset-layout.DocVQA_for_LayoutLM
Dataset Card for "DocVQA_layoutLM_large"
More Information needed
CIVQA-TesseractOCR-LayoutLM
CIVQA TesseractOCR LayoutLM Dataset
The Czech Invoice Visual Question Answering dataset was created with Tesseract OCR and encoded for the LayoutLM.
The pre-encoded dataset can be found on this link: https://huggingface.co/datasets/fimu-docproc-research/CIVQA-TesseractOCR
All invoices used in this dataset were obtained from public sources. Over these invoices, we were focusing on 15 different entities, which are crucial for processing the invoices.
Invoice number
Variable… See the full description on the dataset page: https://huggingface.co/datasets/SpringRollMonster/CIVQA-TesseractOCR-LayoutLM.alwas-analog-layout-dataset
ALWAS Analog Layout Dataset
Synthetic dataset for training ML models in the ALWAS (Analog Layout Workflow Automation System) pipeline.
Dataset Description
4,000 analog IC layout blocks with complete metadata, stage transitions, and labels for:
Hours estimation — actual vs estimated hours
Complexity classification — Low / Medium / High
Bottleneck risk prediction — Low / Medium / High
Completion time prediction — stage-by-stage transition history
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/muthuk1/alwas-analog-layout-dataset.so101-fixed-layout-3camThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so101",
"total_episodes": 53,
"total_frames": 13250,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 50,
"splits": {
"train": "0:53"
},
"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/igor-saprygin/so101-fixed-layout-3cam.xarm6-pick-mustard-bottle-sim-v4-layoutsThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "xarm6",
"total_episodes": 50,
"total_frames": 7694,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 30,
"splits": {
"train": "0:50"
},
"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/crislmfroes/xarm6-pick-mustard-bottle-sim-v4-layouts.rollout_smolvla_so101_lv2_single_cube_to_box_random_layout__green_sync_0723_1027_20260723_102833This 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/geonmin-kim/rollout_smolvla_so101_lv2_single_cube_to_box_random_layout__green_sync_0723_1027_20260723_102833.so101-fixed-layout-vlaThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so101",
"total_episodes": 50,
"total_frames": 12500,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 50,
"splits": {
"train": "0:50"
},
"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/igor-saprygin/so101-fixed-layout-vla.SO101-lv2-single-cube-to-box-random-layout-grasp-correction-v1so101-fixed-layout-lift-vlaThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so101",
"total_episodes": 3,
"total_frames": 750,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 50,
"splits": {
"train": "0:3"
},
"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/igor-saprygin/so101-fixed-layout-lift-vla.layoutlm_sqad
Dataset Card for "layoutlm_sqad"
More Information needed
layoutlmv3-document-qa-v2alayoutlmv3-document-qaCIVQA_EasyOCR_LayoutLM_Validation
CIVQA EasyOCR LayoutLM Validation Dataset
The CIVQA (Czech Invoice Visual Question Answering) dataset was created with EasyOCR, and it is encoded for LayoutLM models. This dataset contains only the validation split. The train part of the dataset can be found on this URL: https://huggingface.co/datasets/fimu-docproc-research/CIVQA_EasyOCR_LayoutLM_TrainThe pre-encoded validation dataset can be found on this link:… See the full description on the dataset page: https://huggingface.co/datasets/fimu-docproc-research/CIVQA_EasyOCR_LayoutLM_Validation.CIVQA_EasyOCR_LayoutLM_Train
CIVQA EasyOCR LayoutLM Train Dataset
The CIVQA (Czech Invoice Visual Question Answering) dataset was created with EasyOCR, and it is encoded for LayoutLM models. This dataset contains only the train split. The validation part of the dataset can be found on this URL: https://huggingface.co/datasets/fimu-docproc-research/CIVQA_EasyOCR_LayoutLM_ValidationThe pre-encoded train dataset can be found on this link:… See the full description on the dataset page: https://huggingface.co/datasets/fimu-docproc-research/CIVQA_EasyOCR_LayoutLM_Train.board_layout_sim_replay_experimentalThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"action": {
"dtype": "float32",
"shape": [
12
],
"names": [
"left_shoulder_pan.pos",
"left_shoulder_lift.pos",
"left_elbow_flex.pos",
"left_wrist_flex.pos",
"left_wrist_roll.pos"… See the full description on the dataset page: https://huggingface.co/datasets/arasi233/board_layout_sim_replay_experimental.