Phi-2 Model
Deep Papers
Comparison of Small Language Models and Large Language Models
This chapter discusses the differences between small language models (SLMs) and large language models (LLMs), emphasizing the benefits of SLMs in terms of trainability with less data, smaller size for local deployment, and ease of fine-tuning for specific tasks. It also examines the infrastructure requirements, parameter sizes, and task specificity associated with LLMs, contrasting their general-purpose nature with the more specialized applications of SLMs.
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