What are Domain-Adapted Models?

‍Domain-adapted models are a type of artificial intelligence model specifically fine-tuned to perform better in a particular domain or application. These models are initially trained on a large, general dataset, and then further trained (or fine-tuned) on data that is more specific to a particular field or topic. This additional training allows the model to better understand the nuances and specifics of this domain – such as the specialized vocabulary, context, or patterns that are unique to it. This process enhances the model's performance in tasks related to that specific domain (such medical text analysis, legal document processing, financial forecasting, etc.).