Mastering LLM Fine-Tuning: A Comprehensive Guide to Synthetic Data Kit The Critical Role of Data Preparation in AI Development Modern language model fine-tuning faces three fundamental challenges: 「Multi-format chaos」: Disparate data sources (PDFs, web content, videos) requiring unified processing 「Annotation complexity」: High costs of manual labeling, especially for specialized domains 「Quality inconsistency」: Noise pollution impacting model performance Meta’s open-source Synthetic Data Kit addresses these challenges through automated high-quality dataset generation. This guide explores its core functionalities and practical applications. Architectural Overview: How the Toolkit Works Modular System Design The toolkit operates through four integrated layers: 「Document Parsing Layer」 Supports 6 …