Datasets:
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license: apache-2.0
task_categories:
- text-generation
language:
- en
tags:
- lean4
- theorem-proving
- code-generation
- benchmark
size_categories:
- n<1K
configs:
- config_name: default
data_files:
- split: train
path: data/train-*.parquet
---
# LeanBench Dataset
A benchmark dataset for evaluating AI systems on Lean 4 theorem proving tasks.
## Dataset Description
This dataset contains **482 tasks** extracted from real Lean 4 pull requests.
## Files
- `leanbench_tasks.csv` - Full dataset in CSV format
- `data/train-00000-of-00001.parquet` - Dataset in Parquet format (for `datasets` library)
## Task Format
Each row represents a single task with the following key fields:
| Field | Description |
|-------|-------------|
| `task_id` | Unique identifier (e.g., LB-0001) |
| `task_type` | Type of task (e.g., pr_completion) |
| `difficulty` | Difficulty level (easy/medium/hard) |
| `difficulty_score` | Numeric difficulty score |
| `repo` | Source GitHub repository |
| `pr_number` | Pull request number |
| `problem_statement` | Natural language description of the task |
| `golden_patch` | Expected solution (diff format) |
| `verification_command` | Command to verify the solution |
## Usage
```python
from datasets import load_dataset
dataset = load_dataset("foundry-ai/leanbench")
# Access tasks
for task in dataset["train"]:
print(task["task_id"], task["difficulty"])
```
## Statistics
- Total tasks: 482
- Easy: 330
- Medium: 121
- Hard: 31
## License
Apache 2.0
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