What is an Encoder-Only model?

An Encoder-only model processes an entire input sequence at once, with every token able to attend to every other token, including ones that come later in the sequence.

• No causal masking, since it's not generating text one token at a time
• Well suited to understanding tasks like classification, sentiment analysis, or extracting information from text, rather than generating new text
• BERT is the best-known example of this architecture family

Encoder-only models excel at deeply understanding a fixed piece of input text, but they aren't naturally built for the open-ended generation task that decoder-only models handle.

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