Guides users through the end-to-end Large Language Model fine-tuning lifecycle using a coach-driven workflow.
The LLM Fine-tuning Coach is a comprehensive workflow engine for Claude Code designed to simplify complex model optimization tasks. It employs a coach-like approach to clarify project goals, manage multiple training tasks, and maintain strict data lineage. From data pipeline configuration and automated benchmark evaluation to deploying fine-tuned models on HuggingFace, it provides a structured framework supporting advanced techniques like LoRA, QLoRA, and DPO, ensuring every training iteration is reproducible and well-documented.
主な機能
01Automated data pipeline configuration with multi-source support
02Full version lineage tracking for data, configs, and model performance
03Coach-driven goal clarification and project scoping agents
04Seamless HuggingFace deployment and benchmark evaluation integration
05End-to-end management of LoRA, QLoRA, and DoRA training workflows
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ユースケース
01Establishing reproducible data pipelines for continuous model improvement
02Comparing multiple model versions and hyperparameter configurations for optimization
03Training domain-specific models with proprietary or synthesized datasets
