Model Card: Assisting Mathematical Formalization with A Learning-based Premise Retriever
Model Description
This model is designed for premise retrieval in Lean, based on the state representation of Lean. The model follows the architecture described in the paper:
Assisting Mathematical Formalization with A Learning-based Premise Retriever
The model implementation and code are available at:
Available Models
The repository provides several models for different tasks:
Pre-trained Models
Located in the Pretrain_Model
folder:
- 410_stable_random: Pre-trained model for retrieval fine-tuning.
- 410_stable_random_1024: Pre-trained model for reranking fine-tuning.
Fine-tuned Models
Retrieval Fine-tuned Models
Located in the Finetune_Model
folder:
- Models fine-tuned on specific datasets for retrieval tasks.
Rerank Fine-tuned Models
Located in the Rerank
folder:
- Models fine-tuned on specific datasets for reranking tasks.
Citation
If you use this model, please cite the following paper:
@misc{tao2025assistingmathematicalformalizationlearningbased,
title={Assisting Mathematical Formalization with A Learning-based Premise Retriever},
author={Yicheng Tao and Haotian Liu and Shanwen Wang and Hongteng Xu},
year={2025},
eprint={2501.13959},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2501.13959},
}
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The HF Inference API does not support sentence-similarity models for transformers library.