Build an AI-powered product tagging system with Amazon SageMaker serverless model customization
- AWS: 91 events in the last 90 days
- Previous: earlier the same day · Announcing instance preference lists for Amazon SageMaker AI training jobs
What happened
Manually tagging thousands of catalog products is slow and inconsistent. This walkthrough shows how to customize Qwen3-8B with supervised fine-tuning (SFT) and reinforcement learning with verifiable rewards (RLVR) on Amazon SageMaker serverless model customization, then deploy it for asynchronous inference to build a cost-efficient product tagging system.
Summary assembled by rule from the sources below