small language models

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Small Language Models (SLMs) are designed to operate with a limited number of parameters, typically ranging from millions to a few billion. This makes them suitable for deployment on devices with lower specifications, such as personal computers and mobile devices. Unlike Large Language Models (LLMs), which require significant memory, processing power, and energy, SLMs offer a more efficient alternative, focusing on agility and cost-effectiveness while maintaining performance ¹³.

The development of SLMs represents a significant shift in the AI landscape, emphasizing quality and efficiency rather than sheer scale. For instance, models like Orca 2, DistilBERT, and the latest Phi-2 have been introduced, showcasing the potential of SLMs to perform specific tasks effectively while requiring less computational resources ³⁴.

Overall, SLMs complement their larger counterparts, providing unique strengths and applications across various fields, making them an essential part of the evolving AI ecosystem ³⁴.

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