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BERT stands for Bidirectional Encoder Representations from Transformers and is designed to pre-train deep bidirectional representations by jointly conditioning on both left and right context in all layers

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Why does everyone use BERT in research instead of LLAMA or GPT or PaLM, etc?

models it takes BERT as a based an adds some kind of fine-tuning or filtering or something. … I don't understand why BERT became the default in research circles when all anyone hears about publicly is GPT-2,3,4 or more recently LLAMA-2. …
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