A Language Model using GPT-2 architecture

A Python-based Retrieval-Augmented Generation system that enhances language model responses by retrieving relevant information from external knowledge sources.

Features

• Custom model architecture for RAG implementation
• Language model wrapper for flexible LLM integration
• Document retrieval and embedding functionality
• Context-aware response generation

Installation

Prerequisites

• Python 3.8 or higher
• pip package manager

Setup

1. Clone the repository:

git clone <your-repo-url>
cd Language_model_RAG

2. Create and activate virtual environment:

python -m venv venv
venv\Scripts\activate  # Windows
source venv/bin/activate  # Mac/Linux

3. Install dependencies:

pip install -r requirements.txt

4. Required packages:

• torch
• numpy
• transformers
• datasets
• accelerate

Usage

Run the main wrapper script:

python lang_wrapper.py

Project Structure

Language_model_RAG/


├── model_architecture.py  # Core RAG model implementation
├── lang_wrapper.py        # Language model interface
├── requirements.txt       # Project dependencies
└── README.md

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.