What are Small Language Models (SLMs)?
14-01-2025
10:15 AM
1 min read

Overview:
Big Tech firms that announced large language AI models also released Small Language Models subsequently.
About Small Language Models (SLMs):
- SLMs represent a specialized subset within the broader domain of artificial intelligence, specifically tailored for Natural Language Processing (NLP).
- SLMs are AI models designed to process and generate human language.
- They're called "small" because they have a relatively small number of parameters compared to large language models (LLMs) like GPT-3.
- SLM is a type of foundation model trained on a smaller dataset compared to LLMs.
- SLMs are characterized by their compact architecture and less computational power.
- This makes them lighter, more efficient, and more convenient for apps that don't have a ton of computing power or memory.
- SLMs are engineered to efficiently perform specific language tasks, with a degree of efficiency and specificity that distinguishes them from their LLM counterparts.
- They are specialized in specific tasks and built with curated, selective data sources.

Q1: What is an example of a SLMs?
An SLM may be tuned and adapted to perform specialized conversational tasks. For example: A programming support agent for specific programming languages, libraries, and use cases. A vision model that can interact with radiologists and extract useful knowledge from medical imagery.
Source: TH