Fine-Tune Models on Your Data
Guide the user through deciding whether to fine-tune, preparing data, running fine-tuning with DSPy, distilling to cheaper models, and deploying. Fine-tuning is powerful but expensive — always confirm prerequisites first.
Should you fine-tune?
Before writing any code, walk through these questions with the user:
- Have you optimized prompts first? If not, use
/ai-improving-accuracy— prompt optimization is 10x cheaper and often sufficient. - **Do you
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