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  ---
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  license: mit
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: mit
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+ inference:
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+ parameters:
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+ max_length: 1024
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+ widget:
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+ - text: "a b : ℕ\n⊢ a + b = b + a"
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+ example_title: "Example"
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  ---
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+
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+ [LeanDojo: Theorem Proving with Retrieval-Augmented Language Models](https://arxiv.org/abs/xxxx.xxxxx)
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+ Under review, NeurIPS (Datasets and Benchmarks Track), 2023
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+ [Kaiyu Yang](https://yangky11.github.io/), [Aidan Swope](https://aidanswope.com/about), [Alex Gu](https://minimario.github.io/), [Rahul Chalamala](https://www.linkedin.com/in/rchalamala),
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+ [Peiyang Song](https://www.linkedin.com/in/peiyang-song-3279b3251/), [Shixing Yu](https://billysx.github.io/), [Saad Godil](https://www.linkedin.com/in/saad-godil-9728353/), [Ryan Prenger](https://www.linkedin.com/in/ryan-prenger-18797ba1/), [Anima Anandkumar](http://tensorlab.cms.caltech.edu/users/anima/)
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+
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+ ```bibtex
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+ @inproceedings{yang2023leandojo,
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+ title={{LeanDojo}: Theorem Proving with Retrieval-Augmented Language Models},
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+ 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},
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+ booktitle={Neural Information Processing Systems (NeurIPS)},
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+ year={2023}
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+ }
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+ ```
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+
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+ Please visit [LeanDojo Website](https://leandojo.org/) for details.
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+
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+ ## Input Format
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+
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+ The model's input consists of retrieved premises concatenated with the current proof state and truncated to 2300 UTF-8 bytes.
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+ The proof state is formatted by Lean's pretty printer, the same as the input format of our [model w/o retrieval](https://huggingface.co/kaiyuy/leandojo-lean3-tacgen-byt5-small).
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+ Retrieved premises are in the form of Lean code, except that proofs are removed and fully qualified names (marked by `<a>...</a>`) are used. Please see the example on the right.
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+
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+