---
license: mit
datasets:
- sxiong/SWAP_v2
language:
- en
base_model:
- meta-llama/Meta-Llama-3-8B-Instruct
---

# **Model Card for SWAP_LLM_v2**

**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**.


## **Model Details**

### **Generator**

* **Base Model:** `meta-llama/Meta-Llama-3-8B-Instruct`
* **LoRA Configuration:**

  * `lora_alpha`: 32
  * `r`: 16
  * `target_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](https://github.com/xiongsiheng/SWAP).


## Citation
```
@inproceedings{xiong-etal-2025-deliberate,
    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",
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.acl-long.1540/",
    doi = "10.18653/v1/2025.acl-long.1540",
    pages = "31900--31931",
    ISBN = "979-8-89176-251-0"
}
```