Which term denotes the family of models capable of performing tasks like translation and question answering, often trained on large datasets?

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Large language models are trained on vast amounts of text and are designed to handle a wide range of language tasks, such as translation and question answering, often by following prompts or being fine-tuned to specific instructions. Their power comes from architectures like transformers that can consider long stretches of text and capture context across sentences and paragraphs, enabling accurate generation and interpretation of language. Other model families include recurrent neural networks, which process sequences step by step, and convolutional neural networks, which are primarily used for image-like data, while generative adversarial networks describe a training setup for generating realistic data rather than the general class of language-focused models. Hence, the term that best fits is large language models.