datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
movement-strict-164
movement-strict-164: High-Quality Filtered Pose Dataset
164,390 clips from Kinetics-700 that pass both programmatic continuity checks and a 235B-parameter Vision-Language Model judge that evaluated the rendered skeleton overlay against the action label. Roughly 60% of clips have been re-tracked through a dedicated multi-frame YOLO + Qwen oracle + sticky IoU tracker pipeline before judgment, replacing the original tracking with a cleaner result.
This is a filtered subset of… See the full description on the dataset page: https://huggingface.co/datasets/maxsegan/movement-strict-164.so101_grey_cylinder_blue_cup_currentcal_transport_corrections16_strict_v1_20260811This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so_follower",
"total_episodes": 16,
"total_frames": 9019,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 30,
"splits": {
"train": "0:16"
},
"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/DylanSh/so101_grey_cylinder_blue_cup_currentcal_transport_corrections16_strict_v1_20260811.mmlu_gneissweb_strict_prunedopen-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens-n8-rejection-sampling-strict-match
N8 Rejection Sampling (Strict Match)
Overview
This dataset was created via rejection sampling from the Qwen3-4B response dataset using Qwen3-32B answers as ground truth.
Source dataset (Qwen3-4B, 8 responses per prompt): marin-community/open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens-n8-reformatted
Verifier dataset (Qwen3-32B, 1 response per prompt): marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens
Creator: The Marin Project… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens-n8-rejection-sampling-strict-match.so101_grey_cylinder_blue_cup_currentcal_precision_replacements7_strict_v1_20260811This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so_follower",
"total_episodes": 7,
"total_frames": 5509,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 30,
"splits": {
"train": "0:7"
},
"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/DylanSh/so101_grey_cylinder_blue_cup_currentcal_precision_replacements7_strict_v1_20260811.so101_grey_cylinder_blue_cup_currentcal_precision_topup16_strict_v2_20260811This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so_follower",
"total_episodes": 16,
"total_frames": 12876,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 30,
"splits": {
"train": "0:16"
},
"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/DylanSh/so101_grey_cylinder_blue_cup_currentcal_precision_topup16_strict_v2_20260811.wish-engine-toolcall-next-v3-strict-general
wish-engine-toolcall-next-v3-strict-general
Wish-engine implementor next-step tool-calling dataset (v3 strict generalization subset, dynamic aliases).
Splits
train.jsonl: 8081980 bytes
validation.jsonl: 1008543 bytes
test.jsonl: 997791 bytes
Schema
Rows are JSONL with at least:
id
messages (chat format with assistant tool_calls)
tool_name
metadata fields (mode, status, trajectory_*)
Notes
Tool names are dynamically aliased per sample.
A tool… See the full description on the dataset page: https://huggingface.co/datasets/sahilmob/wish-engine-toolcall-next-v3-strict-general.cmv_2017_2025_strict_single_turn
CMV 2017-2025: Strictly Single-Turn
This local release is derived from simonycl/cmv_2017_2025_with_persona_0110.
A source row is retained only if neither displayed comment ID occurs in any
positive or negative chain in simonycl/cmv_multi_turn. This guarantees
that neither paired argument is represented in the published multi-turn corpus.
Split counts
Split
Input
Excluded
Retained
train
25962
3779
22183
test
5427
434
4993
expert_train
3075
333
2742… See the full description on the dataset page: https://huggingface.co/datasets/simonycl/cmv_2017_2025_strict_single_turn.so101_processed_clipped_strictThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so101_follower",
"total_episodes": 120,
"total_frames": 45611,
"total_tasks": 4,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 500,
"fps": 30,
"splits": {
"train": "0:120"
},
"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/Taraka84/so101_processed_clipped_strict.omni-retract-era4-strict-recovered-rawau30_tra_strict_clean_highconf_nopunct_absaudio
Strict Cleaned Transcriptions
Source: Sam04/au30_tra
Applied:
punctuation removed from transcription (including Ethiopic punctuation like ።)
removed non-high confidence rows
removed empty rows
removed rows containing latin letters
removed rows containing non-Ethiopic letters
removed rows with < 4 words
removed rows with single-character first/last word
removed exact duplicate-group rows (mode: strip)
converted audio to absolute URLs:… See the full description on the dataset page: https://huggingface.co/datasets/Sam04/au30_tra_strict_clean_highconf_nopunct_absaudio.wish-engine-toolcall-next-v2-strict
wish-engine-toolcall-next-v2-strict
Wish-engine implementor next-step tool-calling dataset (v2 strict canonical subset).
Splits
train.jsonl: 5447561 bytes
validation.jsonl: 679818 bytes
test.jsonl: 672961 bytes
Schema
Rows are JSONL with at least:
id
messages (chat format with assistant tool_calls)
tool_name
metadata fields (mode, status, trajectory_*)
Generated from wish-engine benchmark artifacts by:
scripts/build-hf-toolcall-datasets-v2.mjs
codex-7m-sft-strict-intermediatewish-engine-toolcall-next-v1-strict
wish-engine-toolcall-next-v1-strict
Wish-engine implementor tool-call next-step dataset (strict write-positive subset, v1).
Splits
train.jsonl: 5179089 bytes
validation.jsonl: 557088 bytes
test.jsonl: 772103 bytes
Schema
Rows are JSONL with at least:
id
messages (chat format with assistant tool_calls where applicable)
metadata fields (mode, status, tool_name, etc.)
Generated from wish-engine benchmark artifacts by:
scripts/build-hf-toolcall-datasets-v1.mjs
Westminster-Planning-Decisions-2025
Westminster Planning Decisions 2025 — Officer Reasoning & Policy Citations
A structured sample of 50 planning decision records from Westminster City Council (January–November 2025), extracted from official Decision Notices and Delegated Reports into 37 fields. Built for planning consultants, appeal specialists, BTR/development risk teams, and academics who need to query officer reasoning, refusal grounds, and policy citations across applications — fields that exist as free text in… See the full description on the dataset page: https://huggingface.co/datasets/strictschema/Westminster-Planning-Decisions-2025.wish-engine-toolcall-trajectory-v1-strict
wish-engine-toolcall-trajectory-v1-strict
Wish-engine implementor full tool-call trajectory dataset (strict write-positive subset, v1).
Splits
train.jsonl: 774206 bytes
validation.jsonl: 109100 bytes
test.jsonl: 21480 bytes
Schema
Rows are JSONL with at least:
id
messages (chat format with assistant tool_calls where applicable)
metadata fields (mode, status, tool_name, etc.)
Generated from wish-engine benchmark artifacts by:… See the full description on the dataset page: https://huggingface.co/datasets/sahilmob/wish-engine-toolcall-trajectory-v1-strict.cc100-nepali-strictly-cleaned-devanagari-only
CC-100 Nepali — Cleaned(Devanagari Only)
Pipeline
Unicode normalisation (NFC + ftfy)
Rule-based filters (length, Devanagari ratio ≥ 0.5, boilerplate)
Language ID — fastText lid.176.bin, confidence ≥ 0.7
Exact deduplication (MD5)
Near-deduplication (char 13-gram bloom filter)
98/1/1 train/val/test split, seed 42
Usage
from datasets import load_dataset
ds = load_dataset("Basanta55/cc100-nepali-strictly-cleaned-devanagari-only")
factory-peg-insert-strict-eval-progress
2026-07-23 单进程严格插孔小规模评估
状态
评估已改为 Isaac Lab 与 SmolVLA 同进程运行，避免跨进程相机闭环导致的 Isaac 原生退出。
条件：3 个固定种子（3100--3102），每回合最多 360 步；严格成功为 xy < 2.5 mm 且 held_z - hole_z < 1 mm。
Visual 与 aligned-torque 两组已完成；zero 与 shuffle 在独立 Isaac 重启时因远程 ground-plane USD 不可访问而初始化失败，未被记为失败回合。
已完成结果
条件
严格成功
平均最终 xy
最小 xy
平均最终深度
Visual
0/3
13.425 mm
6.666 mm
16.707 mm
Aligned torque
0/3
27.086 mm
22.640 mm
-2.690 mm
解释边界… See the full description on the dataset page: https://huggingface.co/datasets/Dleshers/factory-peg-insert-strict-eval-progress.curated_dataset_8k_strictsdc-strict-vs-lenient-v1
sdc-strict-vs-lenient-v1
Strict vs lenient pass@1 — strips whitespace and normalizes integer formatting. Shows formatting issues ≠ algorithm failures.
Dataset Info
Rows: 75
Columns: 7
Columns
Column
Type
Description
language
Value('string')
Programming language
tiobe_rank
Value('int64')
TIOBE rank
tiobe_pct
Value('float64')
TIOBE %
tier
Value('string')
Difficulty tier or average
strict_pass_at_1
Value('float64')
Exact match pass@1 %… See the full description on the dataset page: https://huggingface.co/datasets/reasoning-degeneration-dev/sdc-strict-vs-lenient-v1.codex-7m-dpo-strict-intermediatethinkprm-numina-delimited-1k-verification-cots-strictbabylm-binomials-strictnuminamath-cot-four-source-sample-1k-strictWJ_AH_Jailbroken_Only_ORIGIN_strictjudge_success_onlyau30_tra_strict_clean_highconf_nopunct_absaudio_fixed_v2github-issues-vul-detection-gpt-few-strict-vul-desc-resultsprune-step-correct3-strict-v1-zeynepgithub-issues-vul-detection-gpt-few-vul-desc-strict-fixed-resultscurated_dataset_4k_strict