Llama381binstruct Summarize Short Merged

🚀 🧠 FlamingNeuron / llama381binstruct_summarize_short_merged

This is a merged model designed to convert legalese into concise, human - readable summaries. It's based on the NousResearch/Meta - Llama-3.1-8B-Instruct model and fine - tuned with LoRA adapters for legal - domain summarization.

🚀 Quick Start

This model expects Meta - style structured prompts with two fields: original_text and reference_summary. The original_text holds the input passage, and the model generates a summary to replace the empty reference_summary.

For complete setup instructions and working inference examples, see:
👉 GitHub Repo: LLaMA3-demo

✨ Features

• Merged Model: The LoRA weights have been merged with the base model for standalone use.
• Legal Summarization: Converts legalese into short, human - readable summaries based on the legal_summarization project data.

💻 Usage Examples

Basic Usage

This model expects a Meta - style structured prompt. For example:

# Assume you have a function to interact with the model
# Here is a pseudo - code example
input_prompt = {
    "original_text": "Your long legal passage here",
    "reference_summary": ""
}
summary = model.generate_summary(input_prompt)
print(summary)

Advanced Usage

The model can handle more complex legal passages. You can adjust the input text length and complexity according to your needs.

# Assume you have a function to interact with the model
# Here is a pseudo - code example for a more complex input
complex_input = {
    "original_text": "A very long and complex legal passage with multiple clauses...",
    "reference_summary": ""
}
complex_summary = model.generate_summary(complex_input)
print(complex_summary)

🔧 Technical Details

Training Procedure

This model was trained using Supervised Fine - Tuning (SFT) on legal document summaries from the legal_summarization dataset. LoRA adapters were applied during training and merged afterward using merge_and_unload().

Framework Versions

📚 Documentation

Citations

This model was fine - tuned using TRL.

📄 License

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 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).