LLAMA3.2-ENTITY

Introduction

LLAMA3.2-ENTITY is a fine-tuned model based on Llama3.2-3b, designed specifically for extracting names of companies, projects, and people in a specified JSON format. This model aims to anonymize text on a desktop before it is processed in the cloud.

Architecture

The model builds upon the Llama3.2-3b architecture, enhancing its ability to identify and extract specific entities from text data.

Training

The model was trained using unsloth on Google Colab, optimizing its performance for entity extraction tasks.

Guide: Running Locally

To run the LLAMA3.2-ENTITY model locally, follow these steps:

1. Clone the Repository: Download the model files from the Hugging Face Model Hub.
2. Install Dependencies: Ensure you have the required libraries, including PyTorch and GGUF.
3. Load the Model: Use a Python script to load and run the model, enabling entity extraction from your text data.

For optimal performance, consider using cloud GPUs such as those provided by AWS, Google Cloud, or Azure.

License

The LLAMA3.2-ENTITY model is licensed under the Apache-2.0 License, allowing for wide usage and distribution within the terms specified by the license.