What is Fine-tuning?
The process of training a pre-trained model on a smaller, specific dataset to adapt it for a particular task.
Fine-tuning adjusts the weights of an LLM to better perform in a specific domain (like legal or medical) or to adopt a specific style. It differs from RAG, which provides knowledge at runtime; fine-tuning bakes knowledge or behavior into the model itself.
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Retrieval-Augmented Generation (RAG)
A technique that enhances the accuracy and reliability of generative AI models with facts fetched from external sources.
Prompt Engineering
The practice of designing inputs for AI models to produce optimal outputs.
Zero-shot Learning
The ability of a model to perform a task without having seen any specific examples of that task during training.