Write your own training loop — without managing GPUs — with Amazon SageMaker training session APIs
Amazon Web Services Nicolas Jourdan ● Covered by 2 sources
Amazon SageMaker AI added training session APIs that let developers write their own LLM training loop while SageMaker runs the GPU-bound steps as API calls. The article demonstrates a GRPO setup on GSM8K with about 8,500 grade-school math problems. This shifts responsibility so teams only control data, reward/advantage logic, and loop orchestration, while SageMaker handles GPU sampling, gradient updates, checkpointing, and distributed execution with token-based billing.
Why it matters
Amazon SageMaker AI training session APIs let you write your own LLM training loop (SFT, RL, or custom objectives) in a Python script while the service runs the GPUs. This post introduces the programming model and three SDK clients, then walks through a GRPO loop on GSM8K and a reinforcement learning workload on competitive programming.