Running an LLM locally

In this recipe, we will learn how to load an LLM locally using the CPU or GPU and generate text from it after giving it a starting text as seed input. An LLM running locally can be instructed to generate text based on prompting. This new paradigm of generation of text via instruction prompting has brought the LLM to recent prominence. Learning to do this allows for control over hardware resources and environment setup, optimizing performance and enabling rapid experimentation or prototyping with text generation from seed inputs. This enhances data privacy and security, along with a reduced reliance on cloud services, and facilitates cost-effective deployment for educational and practical applications. As we run an LLM locally as part of the recipe, we will use instruction prompting to make it generate text based on a simple instruction.

Getting ready

We recommend that you use a system with at least 16 GB of RAM or a system with a GPU that has at least 8...