Chinchilla Scaling

A training methodology derived from DeepMind's Chinchilla paper showing that many large language models were undertrained relative to their size. Chinchilla scaling laws demonstrate that for a given compute budget, the optimal approach balances model size with training data volume rather than maximizing parameters alone.