The paper describes training GPT-3, an autoregressive language model with 175 billion parameters, which it states is ten times larger than any previous non-sparse language model, and testing it in the few-shot setting.
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Language Models are Few-Shot Learners → states its contribution → The paper describes training GPT-3, an autoregressive language model with 175 billion parameters, which it states is ten times larger than any previous non-sparse language model, and testing it in the few-shot setting.
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