ducanhho2296 / llama_finetuning_qna

This project employs fine-tuning techniques on LLM such as LLamas 2, GPT to develop a specialized Q&A chatbot for enhancing customer services.

Finetune Q&A LLM Chatbot using Amazon Q&A Dataset

link to Colab:

This repository contains the code for a Q&A chatbot application leveraging the GPT-2 model. It is designed to provide intelligent, conversational responses to user queries, making it suitable for applications like customer service, information retrieval, and interactive dialogue systems.

Features

• GPT-2 and BERT Integration: Utilizes the GPT-2 medium variant for generating conversational responses and BERT for question answering capabilities.
• Custom Dataset Handling: Includes scripts for processing and preparing custom datasets for training.
• Efficient Training: Implements a training pipeline using PyTorch and the Hugging Face Transformers library.
• Modular Code Structure: Easy to understand and modify to suit different use-cases or to experiment with different models.

Prerequisites

• Python 3.8 or higher
• PyTorch
• Hugging Face's Transformers library
• Other dependencies listed in requirements.txt

Installation

Clone the repository and install the required packages:

git clone https://github.com/ducanhho2296/LLM_CustomerServiceChatbot.git
cd LLM_CustomerServiceChatbot
pip install -r requirements.txt