datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
minif2f-lean4Fixing the errors in some formal statements and informal proofs of minif2f-lean4.
lean-proofs-v1
Part of the SZL Holdings governed estate — claims are designed to carry checkable receipts. Verification proves integrity & origin, never accuracy or performance.
SZLHOLDINGS/lean-proofs-v1
The complete Lean 4 theorem library for the SZL Holdings Ouroboros Invariant research programme.
Doctrine v10/v11 Canonical Numbers
Metric
Value
Declarations
749
Unique axioms
14 (15 raw, 1 dup)
Sorries
163 (112 baseline + 51 Putnam)… See the full description on the dataset page: https://huggingface.co/datasets/SZLHOLDINGS/lean-proofs-v1.NuminaMath-LEAN-Sol
NuminaMath-LEAN Cleaned with NL Solutions
Dataset Summary
This is a cleaned version of the NuminaMath-LEAN dataset, enhanced with natural language (NL) solutions matched from source datasets. The primary goal is to provide paired formal statements/proofs with natural language solutions for proof formalization and theorem proving research.
The dataset matches problems from NuminaMath-LEAN with their corresponding natural language solutions from:
olympiads-ref: A… See the full description on the dataset page: https://huggingface.co/datasets/iiis-lean/NuminaMath-LEAN-Sol.lean-math-formal-corpus
Lean Math Formal Corpus
This dataset is a unified, compile-validated collection of Lean mathematical problems/proofs aggregated from multiple public sources.
Configs and Lean versions
Different configs correspond to different Lean adaptation versions.
Available configs:
v4.27.0 -> Lean toolchain target leanprover/lean4:v4.27.0 (primary supported version)
v4.15.0 -> Lean toolchain target leanprover/lean4:v4.15.0
v4.9.0 -> Lean toolchain target leanprover/lean4:v4.9.0… See the full description on the dataset page: https://huggingface.co/datasets/iiis-lean/lean-math-formal-corpus.algoveri-lean
AlgoVeri-Lean
77 classical algorithm verification tasks in Lean 4
What is this?
This is the Lean 4 subset of the AlgoVeri benchmark — a cross-language benchmark for vericoding (generating formally verified code from specifications).
Each task provides a Lean 4 specification that includes:
Preconditions — constraints on valid inputs
Function signature — with a sorry'd implementation to be filled in
Postconditions — formal properties the implementation must… See the full description on the dataset page: https://huggingface.co/datasets/lizn-zn/algoveri-lean.proofnet-lean4Leandata
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"])
LeanCat
LeanCat: A Lean Dataset for Evaluating Library-Grounded Category-Theoretic Reasoning
This is an anonymized review artifact.
LeanCat is a dataset of 100 statement-level problems in Lean 4 (mathlib), designed to stress-test abstraction-heavy, library-grounded reasoning in formal mathematics. This repository contains Part I: 1-Category Theory.
Overview
LeanCat addresses a critical gap in automated theorem proving evaluation datasets by focusing on category theory - the… See the full description on the dataset page: https://huggingface.co/datasets/scicraft/LeanCat.leandojohttps://github.com/lean-dojo/LeanDojo
@article{yang2023leandojo,
title={{LeanDojo}: Theorem Proving with Retrieval-Augmented Language Models},
author={Yang, Kaiyu and Swope, Aidan and Gu, Alex and Chalamala, Rahul and Song, Peiyang and Yu, Shixing and Godil, Saad and Prenger, Ryan and Anandkumar, Anima},
journal={arXiv preprint arXiv:2306.15626},
year={2023}
}
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.repro-ai4slt-empirical-processes-in-lean-4-for-formal-statistical-learning-theory-traces
Agent traces
Agent sessions published from a Trackio Logbook.
lean4-stat-learning-theory-novel
A Large-Scale Lean 4 Dataset on Statistical Learning Theory
We present a high-quality, human-verified, large-scale Lean 4 dataset, extracted from our formalization of Statistical Learning Theory (SLT). We present the first comprehensive Lean 4 formalization of SLT grounded in empirical process theory. Our end-to-end formal infrastructure implement the missing contents in latest Lean 4 Mathlib library, including a complete development of Gaussian Lipschitz concentration… See the full description on the dataset page: https://huggingface.co/datasets/yuanhezhang/lean4-stat-learning-theory-novel.LeanBenchmarkdouvras-lean-proof-repair
Douvras Lean Proof Repair Corpus
Exemplos sintéticos de erros comuns de reparo em Lean: importação ausente, incompatibilidade de
tipos, falha de tática, meta não resolvida, reescrita inválida e prova reflexiva. Os snippets não
foram executados no compilador (proof_status: NOT_EXECUTED); portanto o corpus não prova nenhum
teorema e não substitui validação com uma versão específica do Mathlib.
lean4-stat-learning-theory-corpus
A Large-Scale Lean 4 Dataset on Statistical Learning Theory
We present a high-quality, human-verified, large-scale Lean 4 dataset, extracted from our formalization of Statistical Learning Theory (SLT). We present the first comprehensive Lean 4 formalization of SLT grounded in empirical process theory. Our end-to-end formal infrastructure implement the missing contents in latest Lean 4 Mathlib library, including a complete development of Gaussian Lipschitz concentration… See the full description on the dataset page: https://huggingface.co/datasets/yuanhezhang/lean4-stat-learning-theory-corpus.leandojo-benchmark4-v10
LeanDojo Benchmark 4 v10
This repository mirrors the official LeanDojo Benchmark 4 v10 archive used by plan-crl LeanDojo experiments.
Source archive: https://zenodo.org/records/12740403/files/leandojo_benchmark_4.tar.gz?download=1
Metadata from the original archive:
dataset: LeanDojo Benchmark 4
LeanDojo version: 2.0.0
source repository: https://github.com/leanprover-community/mathlib4
source commit: 29dcec074de168ac2bf835a77ef68bbe069194c5
creation time: 2024-07-02 13:14:48.804567… See the full description on the dataset page: https://huggingface.co/datasets/1337xyz1337xyz/leandojo-benchmark4-v10.leanstral-mathlib-calibration-corpora
Leanstral Mathlib calibration corpora
The sample data comes from the pinned Apache-2.0-licensed
Mathlib source tree. This
repository holds the data and curated methods documentation—but not the
separately developed builder package.
This dataset contains the calibration corpora used to pick a static FP8
activation profile for an MXFP4 W4A8 conversion of Leanstral 1.5 119B-A6B. It
publishes every candidate corpus, their manifests, the shared
iterative-development pack, and the… See the full description on the dataset page: https://huggingface.co/datasets/robbiemu/leanstral-mathlib-calibration-corpora.math-lean-hackable-rollouts
Math Lean Hackable Rollouts
This dataset contains 2,241 labeled multi-turn rollouts from a GRPO run on deliberately
hackable Lean 4 theorem-proving tasks. The policy was
nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16.
The run's weakened grader accepts proofs containing sorry; the separate oracle restores
Lean's sorry check. hack_detected is true exactly when the weakened grader paid the
rollout but the restored oracle rejected it. Rows without a gradeable final answer were
excluded… See the full description on the dataset page: https://huggingface.co/datasets/AlignmentResearch/math-lean-hackable-rollouts.lean-repository-midtraining-v1
Lean 4 repository midtraining corpus v1
This is a causal language-model corpus curated from pinned Lean 4 repositories. It is
intended for repository midtraining after introductory Lean language SFT and before
verified proof SFT or verifier-guided RL. The rows contain source text, not
instruction/answer conversations.
Dataset
Split
Chunks
Train
18,367
Validation
1,071
Total
19,438
The source-preserving builder estimates 16.71M tokens using four… See the full description on the dataset page: https://huggingface.co/datasets/Pradheep1647/lean-repository-midtraining-v1.Lean-STaR-plusLeanStatement_CoT
LeanStatement_CoT Dataset Card
Dataset Description
LeanStatement_CoT is a specialized dataset designed for training models to translate mathematical theorems from natural language to Lean4 formal statements, with Chain-of-Thought (CoT) reasoning steps.
Dataset Overview
Task: Natural language to Lean4 theorem translation with CoT reasoning
Size: ~142,000 rows
Format: JSON
License: Apache-2.0
Created by: SJTULean
Data Structure
Fields… See the full description on the dataset page: https://huggingface.co/datasets/SJTULean/LeanStatement_CoT.lean4
💎 Atomic-Lean4-Mathlib: Granular Proofs for Complex Analysis
🚀 Overview
Atomic-Lean4-Mathlib est un dataset de haute fidélité conçu pour le Process Supervision des LLMs de raisonnement (type o1, DeepSeek-R1).
Contrairement aux preuves standard de la Mathlib qui utilisent des tactiques opaques (simp, ring), ce dataset fournit des preuves décomposées à l'atome. Chaque étape logique est explicitée via des blocs calc et des réécritures (rw), permettant aux modèles… See the full description on the dataset page: https://huggingface.co/datasets/7rouz/lean4.PutnamBench-lean4
PutnamBench — Lean 4 (672 problems)
Lean 4 formalizations from PutnamBench,
a benchmark of problems from the William Lowell Putnam Mathematical Competition (1962-2023).
Converted from the official GitHub repository for convenient HuggingFace datasets access.
Citation
@article{tsoukalas2024putnambench,
title={PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical Competition},
author={George Tsoukalas and Jasper Lee and John Jennings and Jimmy Xin… See the full description on the dataset page: https://huggingface.co/datasets/ChristianZ97/PutnamBench-lean4.lean-expert-optimized-2000
lean-expert-optimized-2000
Dataset Description
Optimized 2000-example dataset for training Lean trading algorithm optimization agents with 94%+ success rate target.
Dataset Statistics
Total Examples: 2,000
Training Examples: 1800
Validation Examples: 200
Target Success Rate: 94%+
Expected Performance: 96% (94-98% range)
Category Distribution
JSON Parsing: 1,333 examples (CRITICAL - 0% → 95% impact)
Optimization Workflows: 182 examples (HIGH… See the full description on the dataset page: https://huggingface.co/datasets/Kronu/lean-expert-optimized-2000.LeanStatement_SFT
LeanStatement_SFT Dataset Documentation
Dataset Description
This is a dataset specifically designed to train models to translate mathematical statements from natural language into Lean4 formal theorem statements.
Dataset Summary
Task: Translation from mathematical natural language to Lean4 formal statements
Languages: Natural language (English) → Lean4
Size: Varies by different splits
Creation Date: 2024
Source: Mathematical theorems and problems… See the full description on the dataset page: https://huggingface.co/datasets/SJTULean/LeanStatement_SFT.lean-lean
LeanLean
Can coding agents make a verified Lean library smaller? LeanLean gives an agent 12 hours on each of 64 real-world Lean repositories to compress the Lean codebase as much as it can while preserving the protected theorems.
There are 16 projects per stripped-token band (≤10k, 10k–50k, 50k–250k, >250k): 13.8M stripped tokens and 620 protected declarations in total.
No build artifacts are included. Build a project with lake build, after lake exe cache get for the 63 projects… See the full description on the dataset page: https://huggingface.co/datasets/eth-sri/lean-lean.Leanabell-Prover-Traindata-SFTLeanabell-Prover-Formal-Statementoold-quantities-lean
oold-quantities-lean
What every adapter under this organisation was trained on. Chat-formatted
examples of quantity extraction, generated from the
quantity schemas and rendered to prose.
The prompt is the evaluation prompt
The system message is built by the same function that builds it at evaluation
time, under the same arm, and is character-identical to it. Trained on one
wording and evaluated on another, a result is a wording difference.
Lean means the class… See the full description on the dataset page: https://huggingface.co/datasets/OO-LD/oold-quantities-lean.