Train Your Own LLM from Scratch (github.com)

A new hands-on workshop invites participants to train their own language model (LLM) from scratch using Andrej Karpathy's nanoGPT project. The workshop emphasizes a comprehensive understanding of the LLM training pipeline by guiding learners through each component without relying on black-box libraries. Participants will construct a simplified GPT model with around 10 million parameters that can be trained on a personal laptop in under an hour, ultimately enabling them to generate Shakespeare-like text. This workshop is significant for the AI/ML community as it demystifies the language model training process, providing practical experience with crucial concepts such as tokenizer design, transformer architecture, and the training loop, all through character-level tokenization. The hands-on approach not only enhances participants' technical skills in Python and PyTorch but also empowers them to experiment and innovate within the field. By focusing on smaller datasets and models, the workshop effectively showcases how even minimal setups can yield meaningful results, aligning with broader trends in making AI more accessible and enabling experimentation without requiring extensive resources.