bedrock-fine-tuning

SKILL.md

Complete guide to customizing Amazon Bedrock foundation models through fine-tuning, continued pre-training, reinforcement fine-tuning, and distillation.

Amazon Bedrock Model Customization allows you to adapt foundation models to your specific use cases without managing infrastructure. Four customization approaches are available:

Fine-Tuning (Supervised Learning) Adapt models to specific tasks using labeled examples (input-output pairs). Best for:

Amazon Bedrock Model Customization with fine-tuning, continued pre-training, reinforcement fine-tuning (NEW 2025 - 66% accuracy gains), and distillation. Create customization jobs, monitor training, deploy custom models, and evaluate performance. Use when customizing Claude, Titan, or other Bedrock models for domain-specific tasks, adapting to proprietary data, improving accuracy on specialized workflows, or distilling large models to smaller ones. Source: adaptationio/skrillz.

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