Large Language Models (LLMs) have revolutionized the field of natural language processing (NLP) with their impressive ability to understand context and generate high-quality responses. However, their large number of parameters comes at a cost: high computational demand and longer inference times. To address these challenges, researchers have been exploring Small Language Models (SLMs). Unlike LLMs, […] The post Small Language Models: A Solution to the Limitations of LLMs appeared first on Q...| QBurst Blog
Interest in domain-specific retrieval-augmented generation (RAG) chatbots has peaked in recent months. A major challenge in developing them is ensuring they can answer every question accurately. This problem can be approached in two ways: (1) Add the necessary context in the prompt every time (2) Pre-train the model with the domain knowledge. Each method has […] The post Optimizing Chunk Size and Balancing Context with GPT Models in RAG Chatbots appeared first on QBurst Blog.| QBurst Blog