Elektra is a misspelling of , a major innovation in Natural Language Processing (NLP). Introduced by Google Research in 2020, ELECTRA is a more sample-efficient alternative to traditional language models like BERT. Instead of predicting masked words, ELECTRA uses a "replaced token detection" task: it corrupts the input with plausible alternatives and trains a discriminator to identify which tokens have been swapped. This approach is more compute-efficient, allowing a small ELECTRA model to match the performance of a model that requires significantly more computational power.
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Unlike standard generative models like BERT, ELECTRA uses a "discriminator" to distinguish between real tokens and "fake" ones created by a generator network.