SFT (Supervised Fine-Tuning) is the "job training" a chat model goes through before going live: using thousands of "instruction-response" examples, it...
RAG (Retrieval-Augmented Generation) is a technique that lets a large language model look things up before answering: before generating a response, th...
Knowledge distillation is a technique that lets a small model (the student) learn from an already-trained large model (the teacher). It was formalized...
Chain-of-Thought (CoT) is a prompting technique: instead of letting the model answer directly, you ask it to write out its intermediate reasoning step...
The context window is the upper limit on how many tokens a model can "see" at once: the prompt, the conversation history, retrieved documents, plus th...
The temperature parameter is a sampling parameter that controls how random a large language model's output is. It hides in the advanced settings and A...
Function Calling is the most common mechanism large language models use to reach external capabilities: developers first describe "which functions exi...
GraphRAG is a method that combines knowledge graphs with retrieval-augmented generation. It first extracts entities, relationships, and events from a ...
