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Curious to see what parameter size of gpt3 this will end up being equivalent to. Obviously we won't know until they evaluate their models.


It's trained using the same architecture, and with a very similar dataset, so it should be very close.


My experience is that replicating papers is actually nontrivial. For example someone announced they had replicated gpt2 some time back but when evals were run it turned about to be the equivalent of a much smaller model.




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