Improve dataset card: update task category, add project page, and sample usage

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by nielsr HF Staff - opened
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  ---
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  license: apache-2.0
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  task_categories:
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- - question-answering
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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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- This dataset is used in the paper [Assisting Mathematical Formalization with A Learning-based Premise Retriever](https://huggingface.co/papers/2501.13959). It contains data for training and evaluating a premise retriever for the Lean theorem prover.
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- The dataset is described in detail in the [GitHub repository](https://github.com/ruc-ai4math/Premise-Retrieval). It consists of proof states and corresponding premises from the Mathlib library. The data is designed to train a model to effectively retrieve relevant premises for a given proof state, assisting users in the mathematical formalization process. The dataset is available for download at [this link](https://huggingface.co/datasets/ruc-ai4math/mathlib_handler_benchmark_410).
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+
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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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+
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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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+ ```