Pretraining a modern large language model (LLM), often with ~100B parameters or more, typically involves thousands of accelerators and massive token corpora, running for days to months. At that scale, success is commonly reduced to two headline outcomes: Speed: how fast the system consumes training data, usually measured in tokens/second. Learning: how much progress is […]
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