LLM

TL;DR In this third part of our 4-part series on building language models from scratch, I explore the complete training infrastructure that transforms our clean historical data and custom tokenizer into working language models. Part 1 How to build a Large Language Model from Scratch - covered using the published model Part 2 Building LLMs from Scratch - Part 2: Data Collection & Custom Tokenizers - detailed data collection and custom tokenizer development. Here, we build the complete training pipeline from a custom GPT architecture through deployment-ready checkpoints. ...

TL;DR In this post, I show how to build a working LLM from scratch and show a complete end-to-end pipeline from data gathering to training to deployment of a language model. For this project I concentrate on Old English and only related to London, using historical London texts (1500-1850). To show the flexibility, I built two language models which are identical in architecture and the only differs is their size and parameters (117M vs 354M). ...