The Hidden Challenges of Domain-Adapting LLMs Adapting an LLM to a specific domain might sound straightforward, but it in fact opens a Pandora's box of challenges. Our research team explains the shortfalls of some of the most common techniques.
Case Study: Innovating Domain Adaptation through Continual Pre-Training and Model Merging We show how Arcee uses the most innovative Continual Pre-Training and Model Merging techniques to deliver high-quality domain-specific language models at a fraction of the cost of our competitors–using Medical and Patent data.