The first step in building an LLM is curating a dataset. For a scratch build, this might be a collection of public domain books (e.g., Project Gutenberg) or Wikipedia dumps. The quality of the output is directly proportional to the quality and diversity of the input data.
Training transforms the architecture into a functional assistant. Pretraining: build a large language model from scratch pdf
Building a large language model from scratch involves a deep understanding of machine learning and natural language processing. It requires significant resources and data, as well as careful tuning of model architecture and training procedures. Despite the challenges, the potential applications of these models make them an exciting area of research and development. The first step in building an LLM is curating a dataset