The answer
BERT is an encoder-only model, designed to understand context and fill in missing words, widely used for search and classification.
BERT is an encoder-only model, designed to understand context and fill in missing words, widely used for search and classification.
LSTMs must process words sequentially, one by one. Transformers process all words at once in parallel, leveraging GPU architectures.
A mechanism that scores how relevant other words in the input are to a target word, helping resolve pronoun references (e.g., what 'it' refers to).
GPT is a decoder-only model, optimized for generating text token by token.
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