Fine-tuning a large language model (LLM) like Meta LLAMA 3 involves retraining the model on custom data to reduce inaccuracies and improve output quality. This process includes concepts like quantization to optimize memory usage and LoRA for efficient weight adaptation. The tutorial demonstrates using tools like Unsloth to expedite the training process, providing a step-by-step guide on installing packages, loading models, preparing data, and conducting fine-tuning.
Table of contents
Why do we need to fine tune LLM ?How do we fine tune an LLM ?Fine tuning main conceptsSteps to Fine TuneSort: