api: "YAML JSON TOON Database"
version: "1.0.0"
format: "json"
dataset:
  id: 5
  slug: "llm-glossary"
  title: "Large Language Model Glossary"
  description: "Key terms and concepts in LLM technology: tokens, context windows, temperature, RAG, fine-tuning, quantization, KV cache, and emergence."
  category: "AI & ML Terms"
  category_slug: "ai-ml-terms"
  tags: "llm,ai,glossary,nlp"
  view_count: 0
  created_at: 1777673262
  updated_at: 1777673262
data:
  terms:
    - term: "Token"
      definition: "A unit of text processed by LLMs, typically a word fragment or punctuation"
    - term: "Context Window"
      definition: "Maximum number of tokens an LLM can process in a single inference"
    - term: "Temperature"
      definition: "Sampling parameter controlling randomness in generation (0 = deterministic, >1 = creative)"
    - term: "RAG"
      definition: "Retrieval-Augmented Generation: combining LLMs with external knowledge retrieval"
    - term: "Fine-tuning"
      definition: "Adapting a pre-trained model to specific tasks with additional training"
    - term: "Quantization"
      definition: "Reducing model precision (e.g., FP16 to INT8) to decrease size and increase speed"
    - term: "KV Cache"
      definition: "Key-Value cache storing attention computations for efficient autoregressive generation"
    - term: "Emergence"
      definition: "Capabilities that appear only at certain model scales, not predictable from smaller models"