README.md

---
license: llama3
datasets:
- ai-eldorado/Brazilian_CLT_preferences
language:
- en
- pt
base_model:
- meta-llama/Llama-3.1-8B-Instruct
tags:
- legal
---

**Model Description**  
This repository provides a **LoRA adapter** trained on the same human-preference dataset used for the DPO model. It enables efficient fine-tuning of **LLaMA-3 8B Instruct (4-bit)** for Brazilian labor law applications without requiring full model retraining.

**Intended Use**  
The LoRA adapter is intended for developers and researchers who want to **adapt LLaMA-3 models for CLT-related tasks** while minimizing computational costs. It is particularly useful for **resource-constrained environments** or for integrating into **multi-agent legal assistant systems**.

**Training Details**  
- **Base Model:** LLaMA-3 8B (4-bit quantized)  
- **Method:** LoRA fine-tuning with DPO-aligned dataset  
- **Dataset:** 736 human-preference entries on CLT-related questions  
- **Hyperparameters:** Same as the DPO model  

**Performance Summary**  
When merged with the base model, the LoRA adapter reproduces the improvements observed in the full DPO model:  
- Increased factual accuracy  
- Better semantic alignment with CLT regulations  


#### **Ethical Considerations**
- **Legal Disclaimer:** Not a substitute for professional legal advice.
- **Risk of Misuse:** Incorrect merging or use outside intended domain may lead to inaccurate outputs.
- **Data Privacy:** No personal data was used in training.


#### **Bias and Fairness**
- Same considerations as the DPO model:
  - Regional and interpretation biases may exist.
  - Limited dataset size could affect fairness in edge cases.


#### **Limitations**
- Requires merging with the base LLaMA-3 model for inference.
- Domain-specific; not suitable for general-purpose legal reasoning.


#### **Citation**
```bibtex
@article{moraescomparing,
  title={Comparing RAG, DPO and Agentic Approaches in Systems Performance on Q\&A about Brazilian Labor Legislation},
  author={Moraes, Gabriel K and Luiz, Pedro Augusto and Dias, Gabriel and de Farias, Vitor GCB and Fabiana, CQ de O and Fabris, Vitor L and Vicente, Matheus HR and do Nascimento, Leonardo R and Oliveira, Charles S and dos Santos, Leonardo T and others}
}