How to Fine-Tune Enterprise LLMs on Proprietary Data
Fine-tuning large language models (LLMs) on proprietary enterprise data has become essential for achieving domain-specific performance, especially in regulated or knowledge-heavy industries. General-purpose LLMs often fall short when dealing with specialized terminology, internal procedures, or compliance requirements.
The tuning process typically begins with selecting a base model and applying quantization
