how the transformer model works

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Recently saw a post about AI on here and clicked on a link that explained the transformer model but I couldn’t understand it. Can someone explain it to me like I’m 5?

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2 Answers

Anonymous 0 Comments

A transformer is a neural network – a set of (often complex) algorithms. Most of these algorithms aren’t directly related to linguistics – but probability.

For example, the TF-IDF algorithm (term frequency, inverse document frequency) finds the value of the TF (the frequency of a specific term in a given text) divided by the inverse of the DF (the number of total corpuses containing that term). The higher this value, the more relevant a term is likely to be.

A transformer combines the results of many of these algorithms in order to “comprehend” a given text, and to attempt to produce a relevant response.

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