| | --- |
| | 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. |
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| | **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**. |
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| | **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 |
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| | **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 |
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| | #### **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. |
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| | #### **Bias and Fairness** |
| | - Same considerations as the DPO model: |
| | - Regional and interpretation biases may exist. |
| | - Limited dataset size could affect fairness in edge cases. |
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| | #### **Limitations** |
| | - Requires merging with the base LLaMA-3 model for inference. |
| | - Domain-specific; not suitable for general-purpose legal reasoning. |
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| | #### **Citation** |
| | soon |
