Llama.cpp is a high-performance inference platform designed for Large Language Models (LLMs) like Llama, Falcon, and Mistral. It provides a streamlined development environment compatible with both CPU and GPU systems. This guide explains how to build Llama.cpp into a Docker container image for CPU and GPU systems and push the finished image to a container registry. By the end, you'll have CPU and GPU container images of Llama.cpp built, tagged, and pushed to a container registry.

Prerequisites

A server with Docker installed (a GPU-enabled server with NVIDIA drivers and the NVIDIA Container Toolkit for the GPU build).

Access to the server using SSH.

Start the Docker service.

$ sudo systemctl start docker

Add the non-root user to the Docker group. For example, linuxuser .

$ sudo usermod -aG docker linuxuser

Switch to the user:

$ su - linuxuser

1. Set Up the Project Directory

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