Small Language Models (SLM)

Small language models (SLMs) are designed to perform specific tasks while using fewer resources than larger models (LLM).

SLMs are constructed with fewer parameters and simpler architectures than large language models (LLMs). This design allows for faster training, less energy consumption, and the ability to be deployed on smaller devices like mobile devices.

However, SLMs have a reduced capacity to handle complex language and exhibit lower accuracy, particularly when used outside of their intended focus.

The advantages of using SLMs include lower costs and improved performance in their subject area.