NEWS · COMPANIES · #2439
Amazon SageMaker AI adds training session APIs to run custom training loops on managed GPUs
Amazon has launched SageMaker training session APIs that let developers write custom training loops (SFT, RL, preference optimization, etc.) while SageMaker handles the GPU compute, distribution, checkpointing, and fault recovery. The feature includes three SDK clients in the SageMaker Python SDK, an OpenAI-compatible sampling endpoint, and a published cookbook of SFT and RL recipes (including examples on GSM8K and LoRA workflows).
KEY POINTS
- Amazon has launched SageMaker training session APIs that let developers write custom training loops (SFT, RL, preference optimization, etc.) while SageMaker handles the GPU compute, distribution, checkpointing, and fault recovery.
- The feature includes three SDK clients in the SageMaker Python SDK, an OpenAI-compatible sampling endpoint, and a published cookbook of SFT and RL recipes (including examples on GSM8K and LoRA workflows).
- This lets researchers and engineers retain full algorithmic control over fine-tuning and RL loops without managing GPU infrastructure, speeding iteration and simplifying distributed execution.
WHY IT MATTERS
This lets researchers and engineers retain full algorithmic control over fine-tuning and RL loops without managing GPU infrastructure, speeding iteration and simplifying distributed execution.