An adaptation of the transformer-based GPT (Generative Pre-trained Transformer) model is used by ChatGPT. Unsupervised learning is used to pre-train the model on a sizable text dataset while employing a variant of the transformer architecture. Pre-training teaches the model common linguistic patterns, enabling it to produce text that resembles human speech when customised to a particular task. Moreover, ChatGPT employs a method known as beam search to produce responses, enabling it to produce a number of responses and select the one that is most likely to be relevant depending on the input.
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