Fine-tuning adapts a general-purpose language model to excel at a specific domain. By training on curated examples — legal documents, medical records, procurement contracts — the model learns the vocabulary, patterns, and reasoning style of that field.
At Informatica Systems, we have fine-tuned models including OLMo 2 on an NVIDIA B200 VM, and developed LiveMerge — a cloud platform for merging and customising open-source LLMs like Llama, Mistral, and Qwen without requiring GPUs.
Proper fine-tuning can dramatically improve accuracy, reduce token usage, and eliminate the need for complex prompt engineering. It is the difference between a generalist AI and a specialist that truly understands your business.