FareedKhan-dev/train-llm-from-scratch
Summary
FareedKhan-dev's train-llm-from-scratch article documents a practical pipeline to train language models from scratch using PyTorch, detailing data handling with the Pile, tokenization with the r50k_base tokenizer, and a Transformer-based architecture. It compares training and generation for 13M-parameter and ~2B-parameter models, including sample outputs, training steps, and guidance on scaling and fine-tuning. The content serves as an open-source, hands-on guide for researchers and developers exploring lightweight to mid-sized LLMs.