---
license: other
license_url: https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE
tags:
  - llama3
  - instruction-tuning
  - summarization
  - fine-tuned
  - merged
---

# 🧠 FlamingNeuron / llama381binstruct_summarize_short_merged

This is a **merged model** based on [NousResearch/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3.1-8B-Instruct), fine-tuned using LoRA adapters for legal-domain summarization. The LoRA weights have been merged with the base model for standalone use.

## 🔍 Task

This model converts legalese into short, human-readable summaries, based on data from the [legal_summarization](https://github.com/lauramanor/legal_summarization) project.

## 💡 Example Usage

For complete setup instructions and working inference examples, see:  
👉 [GitHub Repo: LLaMA3-demo](https://github.com/BQ31X/LLaMA3-demo)

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/BQ31X/LLaMA3-demo/blob/main/FlamingNeuron_ModelTest_20250418.ipynb)


This model expects Meta-style structured prompts with two fields: `original_text` and `reference_summary`. 
The `original_text` contains the input passage, and the model generates a summary in place of the empty `reference_summary`.


## 🏋️ Training Procedure

This model was trained using **Supervised Fine-Tuning (SFT)** on legal document summaries using the [legal_summarization](https://github.com/lauramanor/legal_summarization) dataset. LoRA adapters were applied during training and merged afterward using `merge_and_unload()`.

### ⚙️ Framework Versions

- TRL: 0.16.1  
- Transformers: 4.51.3  
- PyTorch: 2.6.0+cu124  
- Datasets: 3.5.0  
- Tokenizers: 0.21.1

## 📚 Citations

This model was fine-tuned using [TRL](https://github.com/huggingface/trl).

## ⚖️ Legal Notice

This model builds on Meta’s LLaMA 3.1 architecture and is governed by the [LLaMA 3.1 Community License](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE). All use must comply with Meta’s [acceptable use policy](https://ai.meta.com/llama/use-policy/).

It was fine-tuned using the [legal_summarization dataset](https://github.com/lauramanor/legal_summarization) for research and educational purposes only.

This model is not intended for commercial use exceeding the limitations described in the Meta license (e.g. more than 700M monthly active users).