Large language model

These models are built using deep learning techniques, particularly neural networks with many layers, which enable them to understand and produce coherent language. LLMs are trained in diverse text, encompassing books, articles, websites, and more, allowing them to learn grammar, context, facts, and nuances of human language.

One of the key characteristics of LLMs is their ability to generate text that is contextually relevant and grammatically correct. They can perform a wide range of language-related tasks, including translation, summarization, question answering, and text completion. LLMs have billions of parameters, which are the weights in the neural network that the model adjusts during training to learn language patterns.