Large Language Models are deep learning models with billions of parameters trained on extensive text corpora. They can perform various natural language tasks including text generation, translation, summarization, and question answering. Examples include GPT-4, Claude, Llama, and Gemini. LLMs use transformer architecture and are typically accessed via APIs or can be run locally when quantized.
🧠 AI & LLMs beginner
LLM (Large Language Model)
AI models trained on massive text datasets to understand and generate human-like text.
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</> Related Terms
Token
The basic unit of text that LLMs process - typically a word, subword, or character.
Context Window
The maximum amount of text (measured in tokens) that an LLM can process in a single interaction.
Fine-tuning
Adapting a pre-trained model to specific tasks or domains by training on specialized data.
Hallucination
When AI models generate plausible-sounding but factually incorrect or fabricated information.
Transformer
Neural network architecture using self-attention mechanisms, the foundation of modern LLMs like GPT and Claude.