Open-source LLMs for text annotation: a practical guide for model setting and fine-tuning

3.5. We further establish that fine-tuning is preferable to few-shot training with a relatively modest quantity of annotated text. Our findings show that fine-tuned open-source LLMs can be effectively deployed in a broad spectrum of text annotation applications. We provide a Python notebook facilitating the application of LLMs in text annotation for other researchers. Supplementary Information: The online version contains supplementary material available at 10.1007/s42001-024-00345-9.