LogicLLaMA Model Card

Model details

LogicLLaMA is a language model that translates natural-language (NL) statements into first-order logic (FOL) rules. It is trained by fine-tuning the LLaMA-7B model on the MALLS dataset.

Model type: This repo contains the LoRA delta weights for direct translation LogicLLaMA, which directly translates the NL statement into a FOL rule in one go. We also provide the delta weights for other modes:

naive correction LogicLLaMA

License: Apache License 2.0

Using the model

Check out how to use the model on our project page: https://github.com/gblackout/LogicLLaMA

Primary intended uses: LogicLLaMA is intended to be used for research.

Citation

@article{yang2023harnessing,
      title={Harnessing the Power of Large Language Models for Natural Language to First-Order Logic Translation}, 
      author={Yuan Yang and Siheng Xiong and Ali Payani and Ehsan Shareghi and Faramarz Fekri},
      journal={arXiv preprint arXiv:2305.15541},
      year={2023}
}