| license: apache-2.0 | |
| task_categories: | |
| - text-ranking | |
| tags: | |
| - math | |
| - formalization | |
| - lean | |
| library_name: datasets | |
| # Premise Retrieval Dataset for Mathematical Formalization | |
| This dataset is used in the paper [Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization](https://huggingface.co/papers/2501.13959). It contains data for training and evaluating a lightweight and effective premise retrieval model for the Lean theorem prover. | |
| ## About the Dataset | |
| The dataset consists of proof states (acting as queries) and corresponding premises extracted from the Mathlib library. It is designed to facilitate the training of models using a contrastive learning framework to embed queries and premises in a latent space. This process aims to enhance retrieval performance through fine-grained similarity calculation and a re-ranking module, ultimately assisting users in the mathematical formalization process. | |
| ## Links | |
| * **Paper:** [Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization](https://huggingface.co/papers/2501.13959) | |
| * **Project Page:** https://premise-search.com/ | |
| * **Code:** The source code and trained models can be found on the [GitHub repository](https://github.com/ruc-ai4math/Premise-Retrieval). | |
| ## Dataset Access | |
| This dataset is available for download at [this link](https://huggingface.co/datasets/ruc-ai4math/mathlib_handler_benchmark_410) on the Hugging Face Hub. | |
| ## Sample Usage | |
| You can load the dataset using the Hugging Face `datasets` library: | |
| ```python | |
| from datasets import load_dataset | |
| dataset = load_dataset("ruc-ai4math/mathlib_handler_benchmark_410") | |
| # To inspect the 'train' split | |
| print(dataset["train"][0]) | |
| ``` |