LLMs
AI model family
An AI model family refers to a group of AI models that share a common architecture, training methodology, or intended use case, but differ in size, specific capabilities, or performance characteristics. Models within a family are typically developed and maintained by the same organization, allowing for knowledge transfer and efficient scaling.
Explanation
AI model families are becoming increasingly common as organizations seek to offer a range of models catering to diverse computational constraints and application requirements. For instance, a model family might include smaller, faster models suitable for edge deployment on mobile devices, alongside larger, more accurate models designed for server-side processing. The models within a family are often pre-trained on the same or similar datasets and may undergo fine-tuning for specific tasks. The use of a common architecture within a model family (e.g., different sized Transformer models) enables knowledge sharing during training, improving efficiency and consistency. Furthermore, it allows developers to easily switch between models within the family based on their performance and resource constraints. Examples include the Llama family from Meta or the Gemini family from Google.