[LLM Integration and Deployment]
What is Retrieval Augmented Generation (RAG)?
RAG is an architecture used to optimize the output of an LLM by retraining the model with domain-specific data.
RAG is a methodology that combines an information retrieval component with a response generator.
RAG is a method for manipulating and generating text-based data using Transformer-based LLMs.
RAG is a technique used to fine-tune pre-trained LLMsfor improved performance.