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HomeData Analytics and VisualizationOpen Source ChatGPT Models: A Step-by-Step Guide

Open Source ChatGPT Models: A Step-by-Step Guide

In this article we will explain how Open Source ChatGPT Models works and how you can run them. We will cover two different open source models, namely Alpaca and GPT4All. The purpose of this article is to provide a detailed explanation of the technical aspects and the steps involved in running them. By the end of this article, you should have a clear understanding of how to use them effectively for your desired applications. As these models are open source, they are available for free usage, and you are not required to use the paid OpenAI API to access them.

Table of Contents

Alpaca

Introduction : Alpaca

A team of researchers from Stanford University developed an open-source language model called Alpaca. It is based on Meta’s large-scale language model LLaMA. The team utilizes OpenAI’s GPT API (text-davinci-003) to fine tune the LLaMA 7 billion (7B) parameters sized model so that it can be executed in budget machines. In other words It is designed to be accessible to academicians and individuals who want to build their own chatbots without the need for expensive hardwares, commercial solutions. It also helps small businesses by making AI more accessible and affordable.

How does Alpaca work

The Stanford team began their research with the smallest language model among LLaMA models, which was the LLaMA 7B model, and pre-trained it with 1 trillion tokens. They started with the 175 human-written instruction-output pairs from the self-instruct seed set. They then used OpenAI API to ask ChatGPT to generate more instructions using the seed set. It is to obtain roughly 52,000 sample conversations, which the team used to further fine-tune the LLaMA models using Hugging Face’s training framework.

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