Update README.md

README.md

@@ -1,3 +1,51 @@
----
-license: llama3
----
+---
+license: llama3
+datasets:
+- ai-eldorado/Brazilian_CLT_preferences
+language:
+- en
+- pt
+base_model:
+- meta-llama/Llama-3.1-8B-Instruct
+tags:
+- legal
+---
+
+### ✅ **Model Card for `ai-eldorado/Brazilian_CLT_lora`**
+**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**
+soon