Language-based models, or language models, are specialized machine learning models designed to understand, generate, and manipulate human language. They rely on large datasets of text and complex algorithms to recognize patterns in syntax, semantics, and context, enabling them to predict words, translate languages, summarize information, and answer questions. These models are foundational in natural language processing (NLP) and are commonly built using deep learning architectures like recurrent neural networks (RNNs), transformers, and variations of these, such as BERT, GPT, and T5.