Run Vicuna Locally on CPU | Step-by-Step Guide

Run Vicuna Locally on CPU | Step-by-Step Guide

Table of Contents

1. Introduction
2. What is a Vehicular Model?
3. The Lama.dot.CPP Port of Facebook's Lava Model
4. Running the Vehicular Model on a CPU Machine
5. Using the Quantized Version of the Vikuna Model from Hugging Face
6. Cloning the Repository
7. Creating a Virtual Environment
8. Activating the Virtual Environment
9. Running the Make Command
10. Downloading the Quantized Version of the Vikuna Model
11. Running the Model

Introduction

In this article, we will explore how to run a vehicular model on a CPU machine. We will begin by understanding what a vehicular model is and then proceed to use the Lama.dot.CPP port of Facebook's Lava model in C++. We will also utilize the quantized version of the Vikuna model from Hugging Face. Throughout this process, we will provide step-by-step instructions to help You run the Vikuna model locally on your CPU machine.

What is a Vehicular Model?

A vehicular model refers to an open-source chatbot that emulates GPT-4 with 90% the performance quality of OpenAI's GPT. The Vikuna model, developed by Fast Chat, involves fine-tuning the Llama model with conversations shared by users. Initial evaluations using GPT-4 as a benchmark Show that Vikuna 13B achieves over 90% quality compared to other models like Llama and Stanford Alpaca.

The Lama.dot.CPP Port of Facebook's Lava Model

To run the vehicular model, we will first clone the repository containing the necessary files and code. By following the provided documentation, we can set up the environment and execute the make command to prepare for running the model.

Running the Vehicular Model on a CPU Machine

Next, we will download the quantized version of the Vikuna model from Hugging Face. This version is suitable for CPU machines and requires around 10GB of RAM. If your machine has less than that, you can opt for the 7 billion version. We will provide the necessary commands to download and save the model inside the designated folder.

Using the Quantized Version of the Vikuna Model from Hugging Face

After downloading the quantized version of the Vikuna model, we will run a command to initialize and start the model. This command allows for configuring various settings such as sampling temperature, instructions, and more. Once the model is up and running, we can Interact with it by asking questions or engaging in conversations.

Cloning the Repository

To begin the installation process, we need to clone the repository containing the necessary files. This can be done by executing the appropriate git clone command in your terminal. By cloning the repository, you will have access to all the required files and code to run the vehicular model.

Creating a Virtual Environment

To ensure a clean and isolated installation, we recommend creating a virtual environment. This helps in managing dependencies and prevents any conflicts with existing packages. The virtual environment can be created using the virtualenv package, and we will provide the commands to set it up.

Activating the Virtual Environment

After creating the virtual environment, we need to activate it before proceeding with the installation. By activating the virtual environment, we ensure that all subsequent commands and installations are limited to the created environment only. We will provide the necessary command to activate the virtual environment.

Running the Make Command

Once the virtual environment is activated, we can run the make command as specified in the documentation. This command sets up the required dependencies and prepares the environment for running the vehicular model. We will guide you through the process of executing the make command.

Downloading the Quantized Version of the Vikuna Model

In order to run the Vikuna model, we need to download the quantized version from Hugging Face. The quantized version is optimized for CPU machines and requires a specific amount of RAM. We will provide the necessary commands to download the model and save it in the designated folder.

Running the Model

After downloading the quantized version of the Vikuna model, we can run a command to initialize and start the model. This command ensures that all the dependencies are in place and sets up the necessary environment variables. Once the model is up and running, we can interact with it by asking questions or engaging in conversations.

In conclusion, this article has provided a comprehensive guide on running a vehicular model on a CPU machine. By following the step-by-step instructions, you can easily set up the environment, download the required files, and start interacting with the model. Running the Vikuna model locally on your machine allows for easy testing and customization.