sxiong/SWAP_v2
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SWAP_LLM_v2 is a suite of supervised fine-tuned models developed for multi-step reasoning with large language models (LLMs). The framework encompasses two primary components: generator and discriminator.
Base Model: meta-llama/Meta-Llama-3-8B-Instruct
LoRA Configuration:
lora_alpha: 32r: 16target_modules: ["up_proj", "down_proj", "gate_proj", "q_proj","k_proj", "v_proj", "o_proj"]bias: "none"Base Model: meta-llama/Meta-Llama-3-8B-Instruct
LoRA Configuration:
lora_alpha: 32r: 16target_modules: ["up_proj", "down_proj", "gate_proj", "q_proj","k_proj", "v_proj", "o_proj"]bias: "none"For additional information and implementation details, please refer to the SWAP GitHub repository.
@inproceedings{xiong2025deliberate,
title={Deliberate reasoning in language models as structure-aware planning with an accurate world model},
author={Xiong, Siheng and Payani, Ali and Yang, Yuan and Fekri, Faramarz},
booktitle={Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
pages={31900--31931},
year={2025}
}
Base model
meta-llama/Meta-Llama-3-8B-Instruct