Also known as: llm · LLM (Large Language Model) · LLM · Large Language Model (LLM) · Large Language Models (LLMs) · Large Language Models
LLM, o modelo de lenguaje grande, es un modelo de lenguaje con un gran número de parámetros entrenado con texto amplio o datos multimodales para comprender y generar lenguaje. Los LLM pueden realizar tareas como responder preguntas, resumir, redactar, programar, traducir y generar texto con apariencia de razonamiento, pero sus resultados requieren evaluación y gobernanza.
A language model with a large number of parameters (typically at least a billion) that are adjusted during training. Due to its size, it requires a lot of data and computing capability to train. Large language models are usually based on the transformer architecture.
A text-driven foundational model that's trained on a vast amount of data. LLMs are used to perform natural language processing (NLP) tasks, such as text generation, machine translation, text summarization, and question answering. LLMs are text-based, whereas foundation models can be trained with and receive input from multiple modalities, including text, images, audio, and video.
A side-by-side comparison of Large Language Model and Language Model. Understand why an LLM is a large-scale form of language model with broader task capabilities and governance needs.
A side-by-side comparison of Large Language Model and Foundation Model. Understand why an LLM is language-centered, while a foundation model is a broad pretrained base model that can support many downstream tasks.
A side-by-side comparison of Generative AI and Large Language Model. Understand why generative AI is a broader content-producing category, while an LLM is a language-focused model type often used inside generative AI systems.