: Balancing model size, training data, and compute power for optimal performance. Fine-tuning and Evaluation Fine-tuning
" by Sebastian Raschka. It provides a step-by-step hands-on journey coding a model in plain PyTorch. build a large language model %28from scratch%29 pdf
: Developing individual components, including embedding layers and attention mechanisms, and combining them into a transformer structure. Training and Pretraining Pretraining : Balancing model size, training data, and compute
: An introduction to what LLMs are, their history, and a high-level overview of the transformer architecture . : Balancing model size