From Evaluation to Deployment — The Complete Fine-tuning Guide
Evaluate with Perplexity, KoBEST, ROUGE-L. Merge adapters with merge_and_unload(), convert to GGUF, deploy via vLLM/Ollama. Overfitting prevention, data quality, hyperparameter guide.
From Evaluation to Deployment — The Complete Fine-tuning Guide
In Part 1 we covered LoRA fundamentals and ran our first fine-tuning. In Part 2 we tackled QLoRA and Korean dataset construction. Training is done. Now two questions remain:
Series: Part 1: LoRA Theory | Part 2: QLoRA + Korean | Part 3 (this post)
- Did the model actually improve? (Evaluation)
- How do we serve it to users? (Deployment)
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