Fine-Tuning Large Language Models
Up to this point, we’ve explored the features and applications of large language models (LLMs) in their “base” form, meaning that we consumed them with the parameters obtained from their base training. We experimented with many scenarios in which, even in their base form, LLMs have been able to adapt to a variety of scenarios. Nevertheless, there might be extremely domain-specific cases where a general-purpose LLM is not sufficient to fully embrace the taxonomy and knowledge of that domain. If this is the case, you might want to fine-tune your model on your domain-specific data.
Definition
In the context of fine-tuning language models, “taxonomy” refers to a structured classification or categorization system that organizes concepts, terms, and entities according to their relationships and hierarchies within a specific domain. This system is essential for making the model’s understanding and...
