datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
qualora-workforce-skills-graph
Qualora Workforce Skills Graph (Representative Sample)
Rights-clean, provenance-tracked vocational learning data, rebuilt from roughly $2B of U.S. Department of Labor funded open courseware into a labeled skills graph: cleaned courses and lessons, Bloom-tagged assessment items with answer rationales and learning objectives, and a content-grounded course to skill to career graph with salary context. Built for post-training and evaluation, not pretraining bulk.
This repository is… See the full description on the dataset page: https://huggingface.co/datasets/qualora-data-labs/qualora-workforce-skills-graph.fin-cfa-graphgen
Fin-CFA-GraphGen: 785K Knowledge-Guided Financial QA Examples
Fin-CFA-GraphGen is a large-scale English dataset for financial instruction tuning, financial question answering, and domain-specific language-model post-training. It contains 785,149 synthetic question–answer examples generated from CFA curriculum and exam-preparation books with the GraphGen knowledge-driven data-generation method.
The dataset and its role in the post-training pipeline are described in Data-Centric… See the full description on the dataset page: https://huggingface.co/datasets/whoisjiji/fin-cfa-graphgen.islamic-corpus-graph
QuranLab — Qur'an & Hadith Structured Corpus and Knowledge Graph
A unified, verse- and ḥadīth-aligned structured corpus for the Qur'an and the canonical Sunnah,
assembled by volunteers under the QuranLab effort. It links Qur'anic verses, multilingual
translations, classical tafsīr, word-level morphology, and ḥadīth text with normalized authenticity
grades into one consistent graph, alongside retrieval passages, grounded question–answer pairs and a
held-out evaluation set. Every… See the full description on the dataset page: https://huggingface.co/datasets/quranlab/islamic-corpus-graph.qualora-workforce-skills-graph
Qualora Workforce Skills Graph (Representative Sample)
Rights-clean, provenance-tracked vocational learning data, rebuilt from roughly $2B of U.S. Department of Labor funded open courseware into a labeled skills graph: cleaned courses and lessons, Bloom-tagged assessment items with answer rationales and learning objectives, and a content-grounded course to skill to career graph with salary context. Built for post-training and evaluation, not pretraining bulk.
This repository is… See the full description on the dataset page: https://huggingface.co/datasets/VegasIGN/qualora-workforce-skills-graph.praxis-chess-evidence-graphs
Praxis Chess Evidence Graphs
Built for, and used to
train and test,
praxis-chess-reasoner-qwen3.5-2b-lora
and its 4B sibling.
Chess mistakes from public Lichess data, each with an evidence graph of
engine-computed facts about the move, and a verified explanation: a typed
reasoning chain that a program can check claim by claim, the labels (what
happened, and why) and two or three sentences of prose.
The dataset exists to test one question: does a small model explain mistakes… See the full description on the dataset page: https://huggingface.co/datasets/praxis-chess/praxis-chess-evidence-graphs.Z3-Verified-Reasoning-Graphs
Z3-Verified Constraint Reasoning Dataset
5k Baseline · Production-Ready · Zero Label Noise
The Problem This Solves
Most synthetic reasoning datasets only show the "happy path". Real reasoning requires knowing when to backtrack.
Open-source LLMs hallucinate on constraint satisfaction problems because they are trained on fluent-sounding but logically inconsistent traces. This dataset is different:
❌ No LLM-generated reasoning — zero hallucinations, zero label noise
✅… See the full description on the dataset page: https://huggingface.co/datasets/nagygabor/Z3-Verified-Reasoning-Graphs.GraphWalkerBenchThis repository contains the GraphWalkerBench dataset from the paper GraphWalker: Agentic Knowledge Graph Question Answering via Synthetic Trajectory Curriculum.
Code: https://github.com/XuShuwenn/GraphWalker
graph-data-quantum-rl
Citation
If you use this dataset, please cite:
@misc{yu2025quasarquantumassemblycode,
title={QUASAR: Quantum Assembly Code Generation Using Tool-Augmented LLMs via Agentic RL},
author={Cong Yu and Valter Uotila and Shilong Deng and Qingyuan Wu and Tuo Shi and Songlin Jiang and Lei You and Bo Zhao},
year={2025},
eprint={2510.00967},
archivePrefix={arXiv},
primaryClass={cs.AI},
url={https://arxiv.org/abs/2510.00967},
}
GraphForge-SFT-2169-clean
GraphForge-SFT-2169
This release contains 2,169 trajectory sequences corresponding to the main
GraphForge SFT corpus for the 27B and 35B-A3B checkpoints. GLM-5.2 teacher
trajectories were admitted with agent-judge score strictly above 0.90.
Both checkpoints were trained for three epochs. This is not the RFT corpus.
Contents
data/train.jsonl retains nested messages, reasoning, tool calls and responses,
task prompts, rubric criteria and file specifications. Original… See the full description on the dataset page: https://huggingface.co/datasets/groundhogLLM/GraphForge-SFT-2169-clean.simson-assembly-dependency-graph
🔗 Simson Assembly Dependency Graph
13 „Braucht-auch"-Ketten für Simson-Reparaturen und Tuning.
Was das ist
Jeder Eintrag beschreibt, was man zusätzlich braucht wenn man ein bestimmtes Teil einbaut:
Pflicht-Teile (mandatory_with): Ohne diese geht es nicht
Empfohlene Teile (recommended_with): Sinnvoll, aber optional
Inkompatible Teile: Was NICHT gleichzeitig verbaut werden kann
Upgrade-Pfad: Was als nächstes Sinn macht
Geschätzte Arbeitszeit & Skill-Level
Kosten:… See the full description on the dataset page: https://huggingface.co/datasets/jmp1987/simson-assembly-dependency-graph.psy-q-graph-369666
psy-q-graph-369666
369,666 synthetic abstract pathway-graph records in PoT-O-style challenge / optimal_path form. Part of the 369.666.444 (Psy-Q-Finder 369M) program. Graphs use fictional node types (meta, route, guard, probe) and weighted edges — not real molecules, CAS IDs, or laboratory procedures.
Paired base model: Tribewarez/psy-q-finder-369M.
Record schema
Field
Meaning
challenge
Single-line graph spec: nodes, edges, start, goal, forbidden edge… See the full description on the dataset page: https://huggingface.co/datasets/Tribewarez/psy-q-graph-369666.simson-unified-knowledge-graph
🧠 Simson Unified Knowledge Graph
173 Nodes × 348 Edges – der Klebstoff zwischen allen Simson-Datasets.
Was das ist
Ein maschinenlesbarer Graph, der alle 6 Datasets miteinander verknüpft:
Dataset
Status
Nodes
racing-planet-simson-traces
Diagnose-Traces
15
simson-forum-qa-pairs
Forum-Wissen
30
simson-repair-manual
Technische Daten
14
racing-planet-product-catalog
Teilekatalog
37
simson-youtube-tutorials
Video-Tutorials
20… See the full description on the dataset page: https://huggingface.co/datasets/jmp1987/simson-unified-knowledge-graph.channel3-universal-product-graph-sample
Channel3 Universal Product Graph (Sample)
Structured, AI-ready product data from across the web. This repository contains a small evaluation sample. The full dataset is available under a commercial license from Channel3.
What this is
Channel3 maintains a universal product graph: a connected, continuously updated dataset of products from across the internet. For each product it provides normalized and comparable titles, stable identifiers for deduplication and… See the full description on the dataset page: https://huggingface.co/datasets/trychannel3/channel3-universal-product-graph-sample.