The text explains how to use mpirun to launch an LLaMA inference job across multiple cloud instances. This allows for more memory-efficient model training and inference, even without a multi-GPU workstation or server. The process involves setting up a cluster of cloud instances with SSH key login, cloning the LLaMA repository, installing dependencies, and running a shell script to automate these steps. Once set up, users can launch interactive inference jobs using mpirun, which allows for faster inference speeds compared to other methods. The cost of running an LLaMA job on Lambda Cloud is also estimated, with costs varying depending on the model size and instance type. Overall, this tutorial provides a practical guide for deploying LLaMA on cloud infrastructure.