Fine-tuning LLMs

Fine-tuning large language models for NLP tasks using standard fine-tuning, LoRA, and quantization.

A collection of experiments fine-tuning large language models for downstream NLP tasks including sentiment analysis and text classification. Covers three adaptation strategies:

  • Standard fine-tuning — full parameter updates
  • LoRA (Low-Rank Adaptation) — efficient parameter-efficient tuning
  • Quantization — reduced-precision inference for deployment

r3lativo/fine-tuning-models