LnRiLWZpZWxke21hcmdpbi1ib3R0b206MC43NmVtfS50Yi1maWVsZC0tbGVmdHt0ZXh0LWFsaWduOmxlZnR9LnRiLWZpZWxkLS1jZW50ZXJ7dGV4dC1hbGlnbjpjZW50ZXJ9LnRiLWZpZWxkLS1yaWdodHt0ZXh0LWFsaWduOnJpZ2h0fS50Yi1maWVsZF9fc2t5cGVfcHJldmlld3twYWRkaW5nOjEwcHggMjBweDtib3JkZXItcmFkaXVzOjNweDtjb2xvcjojZmZmO2JhY2tncm91bmQ6IzAwYWZlZTtkaXNwbGF5OmlubGluZS1ibG9ja311bC5nbGlkZV9fc2xpZGVze21hcmdpbjowfQ==
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
Transformer
A Transformer is a machine learning (ML) model architecture created for multiple tasks, especially in natural language processing (NLP). It transformed NLP by processing input data in parallel, effectively capturing long-range correlations, and enabling deep learning networks to comprehend and produce text.
Share
Related Links
