Reddit user seeks practical advice for fine-tuning Small Language Models

A Reddit user is requesting real-world insights and best practices for fine-tuning Small Language Models (SLMs), specifically focusing on both full fine-tuning and Parameter-Efficient Fine-Tuning (PEFT) methods like LoRA.

The poster aims to enhance an SLM's knowledge in a specific domain, such as marine biology, while preserving its general reasoning capabilities. They are interested in concrete advice regarding dataset curation, selecting appropriate LoRA ranks for different tasks, and strategies for generating synthetic data during Supervised Fine-Tuning (SFT) and alignment stages.

The goal is to integrate the specialized model into a company pipeline as an LLM-as-a-judge or simply to learn fine-tuning techniques effectively.