datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Leandata
LEANDATA
A collection of Lean-formalized STEM problem-solving examples across physics, chemistry, calculus, probability, and related domains.
Dataset summary
Dataset page: https://huggingface.co/datasets/anon-ed-2026/Leandata
Total examples: 580
Loading with datasets
from datasets import load_dataset
ds = load_dataset("anon-ed-2026/Leandata", "atkins")
print(ds["train"][0]["problem_id"])
lawfulbench
LAWFUL-Bench
LAWFUL-Bench: Measuring Whether LLM Agents Apply Data Protection Law
Dheeraj Pai, Lu Xian (Leanmcp)
An agentic benchmark for operational data protection duties under the GDPR.
An agent under test and a simulated data subject each hold tools over one shared
database, and 44 documents of primary law are reachable through
retrieval rather than pasted into the prompt.
The graded artifact is a justification triple -- (decision, lawful_basis, record_action) -- filed… See the full description on the dataset page: https://huggingface.co/datasets/Leanmcp/lawfulbench.lean-proof-or-refute-300
Lean Proof-or-Refute 300
Lean Proof-or-Refute 300 is a compact collection of 300 formal reasoning
problems grounded in Lean 4 and Mathlib. Each problem starts from a verified
Mathlib theorem, makes one small numerical or operator mutation, and asks the
model to return either:
a Lean certificate proving the mutated proposition; or
a Lean certificate proving the exact negation of the complete proposition.
The model receives the related source theorem, a bounded source excerpt… See the full description on the dataset page: https://huggingface.co/datasets/xlr8harder/lean-proof-or-refute-300.Lean4-Changelog-QA
Lean 4 Changelog Q&A Dataset
Dataset Description
The Lean 4 Changelog Q&A Dataset is derived from the Lean4-Changelog. Each Lean 4 changelog entry (including version, section, pull request number, and description) is converted into a single Q&A pair. This allows for straightforward question-answering tasks reflecting the evolution of Lean 4 features, bug fixes, and language decisions over time.
Dataset Structure
Each record contains the following fields:… See the full description on the dataset page: https://huggingface.co/datasets/phanerozoic/Lean4-Changelog-QA.cleand_cw18_lean-six-sigma-cot-500元データ: https://huggingface.co/datasets/cw18/lean-six-sigma-cot-500
使用したコード: https://github.com/LLMTeamAkiyama/0-data_prepare/tree/master/src/lean-six-sigma-cot-500
データ件数: 215
平均トークン数: 514
最大トークン数: 591
合計トークン数: 110,520
ファイル形式: JSONL
ファイル分割数: 1
合計ファイルサイズ: 602.9 KB
加工内容：
文字列長によるフィルタリング:
instruction列（質問）の文字数が6000文字を超える行を除外しました。
output列（思考）の文字数が80000文字を超える行を除外しました。
思考タグの除去と分割:
IS_THINKTAGがFalseに設定されているため、output列をSPLIT_KEYWORD (**Final Toolset… See the full description on the dataset page: https://huggingface.co/datasets/LLMTeamAkiyama/cleand_cw18_lean-six-sigma-cot-500.