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A family of decoder-only Transformer models that are pre-trained to predict the next token on large text corpora, then adapted to downstream tasks.
GPT denotes the generative pre-training recipe introduced by Radford et al. (2018): pre-train a decoder-only Transformer on unlabelled text, then fine-tune. Brown et al. (2020) scaled this to GPT-3 (175B parameters) and showed strong few-shot, in-context learning, establishing the template most modern LLMs follow.
OpenAI's ChatGPT is the best-known product built on this lineage, but "GPT" now broadly names the decoder-only, next-token-prediction approach.
Primary, peer-reviewed and archival sources for this definition.
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