AWS Guide: Preparing Data for Supervised Fine-Tuning
AWS published the first part of a two-part series on preparing data for supervised fine-tuning (SFT). It covers quality checks, conversational JSONL formatting, reasoning and tool-calling schemas, and creating representative train/evaluation splits. The post emphasizes that data preparation determines the ceiling of any SFT project.
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