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Amazon· Bedrock / NovaBuild an AI-powered product tagging system with Amazon SageMaker serverless model customization
Customize Qwen3-8B for product tagging using SageMaker serverless SFT and RLVR training.
Amazon’s walkthrough customizes Qwen3-8B for product tagging with supervised fine-tuning and reinforcement learning with verifiable rewards.
SageMaker serverless model customization manages training; the resulting model is deployed separately to SageMaker Asynchronous Inference.
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In this walkthrough, we customize Qwen3-8B with supervised fine-tuning (SFT), then optimize it with reinforcement learning with verifiable rewards (RLVR) using Group Relative Policy Optimization (GRPO). Amazon SageMaker serverless model customization manages the training capacity
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