datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
genomes-v4-genome_set-animals-intervals-v8_256_128salabs-virtual-spatial-digitaltwin-v8
🌐 SALabs 10,000,000-Node 3D Virtual Spatial & Digital Twin Avatar Kinematics Dataset (v8.0)
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🌟 Executive Summary
The… See the full description on the dataset page: https://huggingface.co/datasets/suitai/salabs-virtual-spatial-digitaltwin-v8.lm-eval-results-bobofrut-ladybird-base-7B-v8-private
Dataset Card for Evaluation run of bobofrut/ladybird-base-7B-v8
Dataset automatically created during the evaluation run of model bobofrut/ladybird-base-7B-v8
The dataset is composed of 62 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An… See the full description on the dataset page: https://huggingface.co/datasets/nyu-dice-lab/lm-eval-results-bobofrut-ladybird-base-7B-v8-private.lm-eval-results-zhengr-MixTAO-7Bx2-MoE-v8.1-private
Dataset Card for Evaluation run of zhengr/MixTAO-7Bx2-MoE-v8.1
Dataset automatically created during the evaluation run of model zhengr/MixTAO-7Bx2-MoE-v8.1
The dataset is composed of 62 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An… See the full description on the dataset page: https://huggingface.co/datasets/nyu-dice-lab/lm-eval-results-zhengr-MixTAO-7Bx2-MoE-v8.1-private.zeroin-v8-r4-dataset
Zeroin Methodology v8-r4 QA
Training corpus used to fine-tune
KG-ZEROIN/gpt-oss-20b-zeroin-v8-r4.
The corpus captures question/answer pairs derived from the Zeroin
fund-evaluation methodology Korean domain document. It is organized
as a Harmony-ready chat-messages dataset for supervised full
fine-tuning of
openai/gpt-oss-20b.
Released under CC BY-NC 4.0 — free for non-commercial research,
evaluation, and educational use. See LICENSE and NOTICE.
Contents
File… See the full description on the dataset page: https://huggingface.co/datasets/KG-ZEROIN/zeroin-v8-r4-dataset.Lunzima__NQLSG-Qwen2.5-14B-MegaFusion-v8-details
Dataset Card for Evaluation run of Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v8
Dataset automatically created during the evaluation run of model Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v8
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 3 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/Lunzima__NQLSG-Qwen2.5-14B-MegaFusion-v8-details.Lunzima__NQLSG-Qwen2.5-14B-MegaFusion-v8.9-details
Dataset Card for Evaluation run of Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v8.9
Dataset automatically created during the evaluation run of model Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v8.9
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/Lunzima__NQLSG-Qwen2.5-14B-MegaFusion-v8.9-details.zhengr__MixTAO-7Bx2-MoE-v8.1-details
Dataset Card for Evaluation run of zhengr/MixTAO-7Bx2-MoE-v8.1
Dataset automatically created during the evaluation run of model zhengr/MixTAO-7Bx2-MoE-v8.1
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/zhengr__MixTAO-7Bx2-MoE-v8.1-details.baab-next-v8-rawpankajmathur__orca_mini_v8_1_70b-details
Dataset Card for Evaluation run of pankajmathur/orca_mini_v8_1_70b
Dataset automatically created during the evaluation run of model pankajmathur/orca_mini_v8_1_70b
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/pankajmathur__orca_mini_v8_1_70b-details.Dataset_Robot_IA_full_v8Lyrical_MT_ru2en_SFT_v8.1_w_solving4gemma4
SilverAgePoets.com & RuVERSES.com Russian-English Bilingual Poetry Library
A dataset of Eastern European and Soviet poetry and song lyrocs from https://RuVerses.com/, with Russian-language sources and English translations.
This variant of the dataset combines a revised and somewhat pre-filtered version of the RuVerses collection dataset + the entirety of the SFT version of our LYRICAL dataset.
Featuring a present (c. early 2026) state of the RuVerses archive, this dataset… See the full description on the dataset page: https://huggingface.co/datasets/AlekseyCalvin/Lyrical_MT_ru2en_SFT_v8.1_w_solving4gemma4.simon-arc-solve-symmetry-v8
Version 1
ARC-AGI Tasks where the job is to transform symmetric images.
example count: 2-4.
test count: 1-2.
image size: 2-3.
symmetry types: hstack2, hstack3, vstack2, vstack3, grid2x2.
Version 2
image size: 2-4.
Version 3
Added HSTACK4, VSTACK4.
Version 4
Added HSTACK5, VSTACK5.
Version 5
Added ImageSymmetrySquare, so images can be rotated by 90 degrees, and flipped over the diagonals.
Version 6
Only exercising… See the full description on the dataset page: https://huggingface.co/datasets/neoneye/simon-arc-solve-symmetry-v8.supportGPT-v8Lil-R__PRYMMAL-ECE-7B-SLERP-V8-details
Dataset Card for Evaluation run of Lil-R/PRYMMAL-ECE-7B-SLERP-V8
Dataset automatically created during the evaluation run of model Lil-R/PRYMMAL-ECE-7B-SLERP-V8
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/Lil-R__PRYMMAL-ECE-7B-SLERP-V8-details.blueteam-v8
Blue_team_v8
Synthetic fine-tuning dataset generated with Dataset Genie 0.1.0 on 2026-09-21T15:02:28+00:00.
Domain brief
Blue-team is broad. Cover these deliberately, spread across difficulty tiers:
Platforms, not one vendor. Splunk (SPL), Microsoft Sentinel (KQL), Elastic (ES|QL/EQL/Lucene), CrowdStrike, Defender for Endpoint, Sysmon, Zeek/Suricata. Identity: Entra ID, Okta, Active Directory/Kerberos. Cloud: AWS (CloudTrail/GuardDuty), Azure, GCP. OS: Windows… See the full description on the dataset page: https://huggingface.co/datasets/k3nn3dy/blueteam-v8.buildeng-v8-3b
BuildEng V8 3B Dataset
This is the dataset holder for the BuildEng 3B branch.
The 3B branch is planned as the stronger local checkpoint after BuildEng 1.5B and before the larger BuildEng 32B model.
Files will be added on June 4.
Author: Irfan Uruchi
Lyrical_MT_ru2en_SFT_v8_with_meter_solving
SilverAgePoets.com & RuVERSES.com Russian-English Bilingual Poetry Library
Our curated dataset of translated Eastern European and Soviet poetry and song lyrics from SilverAgePoets.com and RuVerses.com/.
The dataset features Russian-language sources, English translations, scansion information (meter/foot, rhythm, rhyme), and concisely sketched multistep source-to-target adaptation workflows (formatted as thinking traces).
This variant of the dataset combines a revised and somewhat… See the full description on the dataset page: https://huggingface.co/datasets/AlekseyCalvin/Lyrical_MT_ru2en_SFT_v8_with_meter_solving.Lunzima__NQLSG-Qwen2.5-14B-MegaFusion-v8.7-details
Dataset Card for Evaluation run of Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v8.7
Dataset automatically created during the evaluation run of model Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v8.7
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/Lunzima__NQLSG-Qwen2.5-14B-MegaFusion-v8.7-details.buildeng-v8-1.5b
BuildEng V8 1.5B
BuildEng V8 1.5B is a civil/building engineering dataset made for Qwen2.5-1.5B-Instruct and focused on conservative structural reasoning and construction-related decision making.
The dataset covers reinforced concrete, steel, masonry, shallow foundations, retaining walls, slabs, beams, columns, temporary works, excavation safety, waterproofing, settlement, lateral stability, structural connections, cracking behavior, renovation uncertainty, and construction… See the full description on the dataset page: https://huggingface.co/datasets/Irfanuruchi/buildeng-v8-1.5b.loop-qwen-v8-sft
loop-qwen-v8 SFT dataset (Gemini insulin-control distillation)
8,222 chat-format examples used to SFT loop-qwen-v8 (Qwen3-4B insulin
controller distilled from Gemini-3-flash-preview). Each example is a closed-loop
dosing decision.
Format (JSONL, one chat per line)
system: controller spec (IOB-aware, Chain-of-Draft reason-before-act)
user: patient metadata (age, weight, TDD, CF, IC, basal) + 6h history of CGM / insulin / carbs, as JSON
assistant: JSON… See the full description on the dataset page: https://huggingface.co/datasets/jxx123/loop-qwen-v8-sft.slm-workflow-planner-v8-datasetorca_mini_v8_sharegpt_formatBest 45K samples of Bigger Orca Mini dataset in sharegpt format, Enjoy!
sokoban_easy_v8_noncot_chunk_k10_world_model_20260622_perseg
sokoban_easy_v8_noncot_chunk_k10_world_model_20260622_perseg
Sokoban action-conditioned visual world-model SFT data (non-CoT baseline) for the BAGEL-7B-MoT
VLM-Gym feedback-interval study.
Format: gzipped JSONL shards under training/, one packed row = one episode. Frames are
base64 JPEG (q95). Per-segment CoT layout: <think> per-step imagined frame (MSE target) </think>
then the committed action chunk; between chunks a loss-0 "Action executed." + real frame
(GT re-grounding).… See the full description on the dataset page: https://huggingface.co/datasets/ultrastar111/sokoban_easy_v8_noncot_chunk_k10_world_model_20260622_perseg.synthetic_Jailbreak_Defense_Doorpage_v8
synthetic_Jailbreak_Defense_Doorpage_v8
Silicon Factory v3 - Synthetic Dataset
Entries: 5
Category: mixed
Avg Response Length: 447 chars
Focus: AI JAILBREAK DEFENSE
Mode: Doorpage (auto-gen + fine-tune)
License
MIT
Generated With
Tree-Speculative Decoding
4D Brane Memory for consistency
Quality control & deduplication
Contact & Custom Orders
Custom datasets available. Contact for pricing.
sokoban_easy_v8_noncot_chunk_k5_world_model_20260622_perseg
sokoban_easy_v8_noncot_chunk_k5_world_model_20260622_perseg
Sokoban action-conditioned visual world-model SFT data (non-CoT baseline) for the BAGEL-7B-MoT
VLM-Gym feedback-interval study.
Format: gzipped JSONL shards under training/, one packed row = one episode. Frames are
base64 JPEG (q95). Per-segment CoT layout: <think> per-step imagined frame (MSE target) </think>
then the committed action chunk; between chunks a loss-0 "Action executed." + real frame
(GT re-grounding).… See the full description on the dataset page: https://huggingface.co/datasets/ultrastar111/sokoban_easy_v8_noncot_chunk_k5_world_model_20260622_perseg.myanmar_11k_v8
Dataset Card for myanmar_11k_v8
Dataset Summary
ဒီ dataset က myanmar_11k_v8 အတွက် ဖန်တီးထားတာပါ။
Languages
Myanmar (my) / English (en)
Dataset Structure
Data Instances
{ "text": "နမူနာ စာသား", "label": "အညွှန်း" }
Data Fields
text: main content, label: optional.
Data Splits
Split
Files
train
myanmar_11k_v8.jsonl
Licensing Information
ဒီ dataset က CC BY-NC… See the full description on the dataset page: https://huggingface.co/datasets/kkomyoeminaung/myanmar_11k_v8.sokoban_easy_v8_noncot_chunk_k3_world_model_20260622_perseg
sokoban_easy_v8_noncot_chunk_k3_world_model_20260622_perseg
Sokoban action-conditioned visual world-model SFT data (non-CoT baseline) for the BAGEL-7B-MoT
VLM-Gym feedback-interval study.
Format: gzipped JSONL shards under training/, one packed row = one episode. Frames are
base64 JPEG (q95). Per-segment CoT layout: <think> per-step imagined frame (MSE target) </think>
then the committed action chunk; between chunks a loss-0 "Action executed." + real frame
(GT re-grounding).… See the full description on the dataset page: https://huggingface.co/datasets/ultrastar111/sokoban_easy_v8_noncot_chunk_k3_world_model_20260622_perseg.simon-arc-mass-v8
Version 1
Measure the mass of objects for pixel connectivity 4 and pixel connectivity 8.
image size: 1-10.
max_mass: 4.
Version 2
image size: 1-20.
max_mass: 5.
This converged too slowly. I was too optimistic. I will have to proceed slower.
Version 3
image size: 1-12.
max_mass: 5.
Too big spikes in the training loss. I will have to lower the max_mass, and gradually increase it.
Version 4
image size: 1-15.
max_mass: 2.
The validation loss for this is… See the full description on the dataset page: https://huggingface.co/datasets/neoneye/simon-arc-mass-v8.sokoban_easy_v8_cot_chunk_kinf_world_model_20260707_perseg
sokoban_easy_v8_cot_chunk_kinf_world_model_20260707_perseg
Sokoban action-conditioned visual world-model SFT data (CoT self-rollout) for the BAGEL-7B-MoT
VLM-Gym feedback-interval study.
Format: gzipped JSONL shards under training/, one packed row = one episode. Frames are
base64 JPEG (q95). Per-segment CoT layout: <think> per-step imagined frame (MSE target) </think>
then the committed action chunk; between chunks a loss-0 "Action executed." + real frame
(GT re-grounding). See… See the full description on the dataset page: https://huggingface.co/datasets/ultrastar111/sokoban_easy_v8_cot_chunk_kinf_world_model_20260707_perseg.