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In 2017, researchers at Google introduced the transformer architecture, that has been used to develop huge language designs, like the ones that power ChatGPT. In purely natural language processing, a transformer encodes Every word within a corpus of textual content like a token after which generates an consideration map, which captures each token’s relationships with all other tokens. This interest map allows the transformer realize context when it generates new text.

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