Explore the process of training a small Language Model (LLM) - specifically a base GPT2 with 117 million parameters - on a local computer. Delve into the challenges associated with training LLMs from scratch and understand why this task is primarily undertaken by large organizations. Learn about the intricacies of LLM training, including data preparation, model architecture, and computational requirements. Gain insights into the LLMOPS (Language Model Operations) workflow and its importance in the field of machine learning and data science. Access accompanying notebooks on GitHub to follow along with the practical implementation. This 53-minute video provides a comprehensive look at the complexities and considerations involved in training and deploying smaller-scale language models.