datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Expert-Sudoku-100kwire_harness_expert_sac
Wire Harness Expert SAC
Expert-policy trajectories collected from the five-mover WireHarness MuJoCo
environment for visual world-model training.
Dataset summary
20,000 episodes
3,491,570 stored observation rows
At most 300 environment transitions per episode (up to 301 stored rows,
including the initial observation)
224 x 224 RGB observations, stored as JPEG bytes in pixels
10-dimensional continuous actions
451-dimensional observations
Five task stages and… See the full description on the dataset page: https://huggingface.co/datasets/faridganbarli/wire_harness_expert_sac.IC_SHM_Expert_2
IC-SHM Expert 2 Public Augmentation
This repository contains the public-data augmentation used for IC-SHM
Expert 2 and the final Qwen3-VL-8B LoRA adapter. The original competition
images and annotations are not redistributed.
Training code and the complete experiment documentation are available at
https://github.com/HKUJasonJiang/IC-SHM-Expert-2.
Dataset contents
Added class
Images
concrete_crack
50
efflorescence
200
Total
250
Each image has… See the full description on the dataset page: https://huggingface.co/datasets/JasonXF/IC_SHM_Expert_2.bipea-expert-nogpqa-v3
BIPEA expert data
Source datasets
C4
WikiText-103
SlimPajama
OpenWebMath
CodeSearchNet
gomodel-go-expert-v4
GoModel Go Expert v4 Dataset
Description
A high-quality dataset for fine-tuning Qwen2.5-Coder-7B to be an expert Go software engineer
with tool-calling capabilities. This is version 4, substantially rebuilt from v3 with:
Structured messages format (not pre-rendered ChatML text)
Go AST-extracted code from real repositories using go/parser
Go 1.26 feature coverage (February 2026 release)
Senior/staff-level engineering content (architecture, distributed systems, API… See the full description on the dataset page: https://huggingface.co/datasets/mencosk/gomodel-go-expert-v4.urban-vla-expert-v1
Urban VLA Expert v1
Urban VLA Expert v1 is a simulator dataset for language-conditioned urban driving. Each frame pairs a 256 x 256 front-camera image with ego state, a natural-language instruction, and continuous driving controls.
This is a small research dataset, not evidence that a policy is ready for a real vehicle. The expert is a deterministic simulator controller, and the language prompts are curated paraphrases rather than speech collected from drivers.
What… See the full description on the dataset page: https://huggingface.co/datasets/Mayank022/urban-vla-expert-v1.ontocord__wide_3b_sft_stage1.2-ss1-expert_news-details
Dataset Card for Evaluation run of ontocord/wide_3b_sft_stage1.2-ss1-expert_news
Dataset automatically created during the evaluation run of model ontocord/wide_3b_sft_stage1.2-ss1-expert_news
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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/ontocord__wide_3b_sft_stage1.2-ss1-expert_news-details.gomodel-go-expert-v7repro-multi-agent-teams-hold-experts-back-traces
Agent traces
Agent sessions published from a Trackio Logbook.
ontocord__wide_3b_sft_stage1.2-ss1-expert_fictional_lyrical-details
Dataset Card for Evaluation run of ontocord/wide_3b_sft_stage1.2-ss1-expert_fictional_lyrical
Dataset automatically created during the evaluation run of model ontocord/wide_3b_sft_stage1.2-ss1-expert_fictional_lyrical
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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/ontocord__wide_3b_sft_stage1.2-ss1-expert_fictional_lyrical-details.ontocord__wide_3b_sft_stage1.2-ss1-expert_how-to-details
Dataset Card for Evaluation run of ontocord/wide_3b_sft_stage1.2-ss1-expert_how-to
Dataset automatically created during the evaluation run of model ontocord/wide_3b_sft_stage1.2-ss1-expert_how-to
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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/ontocord__wide_3b_sft_stage1.2-ss1-expert_how-to-details.flatmate-rl-expert-trajectoriesgomodel-go-expert-v3
GoModel Go Expert v3
Dataset description
GoModel Go Expert v3 is an English instruction and completion dataset for training
Go coding assistants. It combines curated production Go, code-specific synthetic
tasks, and agentic tool trajectories. Every JSONL record contains a full
Qwen2.5-compatible ChatML conversation in its text field.
Key changes from v2
Tool calls now use Qwen2.5's native <tool_call> tags instead of bare JSON.
Tool definitions use… See the full description on the dataset page: https://huggingface.co/datasets/mencosk/gomodel-go-expert-v3.gomodel-go-expert-v2
GoModel Go Expert v2
Dataset description
GoModel Go Expert v2 is an English instruction and completion dataset for training
Go coding assistants. It combines curated production Go with synthetic instruction
tasks and agentic tool trajectories. Version 2 is a new dataset and does not replace
the earlier GoModel repositories. Each JSONL record is already serialized as a full
Qwen-compatible ChatML conversation in its text field.
Data sources
Source… See the full description on the dataset page: https://huggingface.co/datasets/mencosk/gomodel-go-expert-v2.ontocord__merged_0.2_expert_0.8-details
Dataset Card for Evaluation run of ontocord/merged_0.2_expert_0.8
Dataset automatically created during the evaluation run of model ontocord/merged_0.2_expert_0.8
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.… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/ontocord__merged_0.2_expert_0.8-details.ontocord__merged_0.5_expert_0.5-details
Dataset Card for Evaluation run of ontocord/merged_0.5_expert_0.5
Dataset automatically created during the evaluation run of model ontocord/merged_0.5_expert_0.5
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.… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/ontocord__merged_0.5_expert_0.5-details.mixture-of-experts-papers
Mixture of Experts Papers — FineSet
A research-paper dataset on Mixture of Experts Papers, assembled, deduplicated, and quality-scored by
FineSet from arXiv and Semantic Scholar.
📸 This is a dated snapshot — generated 2026-06-19.
It is not auto-updated. Research on Mixture of Experts Papers moves fast — new papers land on arXiv every
week. Want this same dataset refreshed daily, on a topic you choose? See the bottom. ↓
Why this dataset
Quality-scored:… See the full description on the dataset page: https://huggingface.co/datasets/fineset-io/mixture-of-experts-papers.ontocord__merged_0.2_expert_0.8-stack_2x-details
Dataset Card for Evaluation run of ontocord/merged_0.2_expert_0.8-stack_2x
Dataset automatically created during the evaluation run of model ontocord/merged_0.2_expert_0.8-stack_2x
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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/ontocord__merged_0.2_expert_0.8-stack_2x-details.ontocord__wide_3b_sft_stage1.2-ss1-expert_software-details
Dataset Card for Evaluation run of ontocord/wide_3b_sft_stage1.2-ss1-expert_software
Dataset automatically created during the evaluation run of model ontocord/wide_3b_sft_stage1.2-ss1-expert_software
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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/ontocord__wide_3b_sft_stage1.2-ss1-expert_software-details.ontocord__wide_3b_sft_stage1.2-ss1-expert_formatted_text-details
Dataset Card for Evaluation run of ontocord/wide_3b_sft_stage1.2-ss1-expert_formatted_text
Dataset automatically created during the evaluation run of model ontocord/wide_3b_sft_stage1.2-ss1-expert_formatted_text
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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/ontocord__wide_3b_sft_stage1.2-ss1-expert_formatted_text-details.ontocord__wide_3b_sft_stage1.2-ss1-expert_math-details
Dataset Card for Evaluation run of ontocord/wide_3b_sft_stage1.2-ss1-expert_math
Dataset automatically created during the evaluation run of model ontocord/wide_3b_sft_stage1.2-ss1-expert_math
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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/ontocord__wide_3b_sft_stage1.2-ss1-expert_math-details.Minimal-Hopper-Expert-v5Hopper-Expert-v5loomstack-compact-expertHalfCheetah-Expert-v2Minimal-Walker2d-Expert-v5Minimal-HalfCheetah-Expert-v5Walker2d-Expert-v5HalfCheetah-Expert-v5