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AWS Machine Learning Blog· Nicolas Jourdan·· 24 d ago

Write your own training loop — without managing GPUs — with Amazon SageMaker training session APIs

Write your own training loop — without managing GPUs — with Amazon SageMaker training session APIs

AI summary

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.

Selection record

Not admittedSum of both 116 < twice the threshold 120

Source tier
Official, first-hand; this tier's threshold is 60
Pre-filter
passed:SageMaker训练会话API用于LLM微调与RL训练

A model scores each item twice, independently, against one written standard, out of 100. An item is admitted only when the two scores add up to twice the threshold. The threshold is set per source tier.

Source: AWS Machine Learning Blog · aws.amazon.com