Improve dataset card: update task category, add project page, and sample usage
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by
nielsr
HF Staff
- opened
README.md
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license: apache-2.0
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task_categories:
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tags:
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- math
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- formalization
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- lean
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---
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---
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license: apache-2.0
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task_categories:
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- text-ranking
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tags:
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- math
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- formalization
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- lean
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library_name: datasets
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---
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# Premise Retrieval Dataset for Mathematical Formalization
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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.
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## About the Dataset
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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.
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## Links
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* **Paper:** [Learning an Effective Premise Retrieval Model for Efficient Mathematical Formalization](https://huggingface.co/papers/2501.13959)
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* **Project Page:** https://premise-search.com/
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* **Code:** The source code and trained models can be found on the [GitHub repository](https://github.com/ruc-ai4math/Premise-Retrieval).
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## Dataset Access
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This dataset is available for download at [this link](https://huggingface.co/datasets/ruc-ai4math/mathlib_handler_benchmark_410) on the Hugging Face Hub.
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## Sample Usage
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You can load the dataset using the Hugging Face `datasets` library:
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```python
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from datasets import load_dataset
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dataset = load_dataset("ruc-ai4math/mathlib_handler_benchmark_410")
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# To inspect the 'train' split
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print(dataset["train"][0])
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```
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