google-research/electra
ELECTRA is a self-supervised method for pre-training transformer text encoders using a discriminator that distinguishes real tokens from generated fakes.

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The repository provides code to pre-train ELECTRA models, including small models trainable on a single GPU, and supports fine-tuning on downstream NLP tasks including GLUE classification, SQuAD question answering, and sequence tagging. It also includes Electric, an energy-based version of ELECTRA that can produce pseudo-likelihood scores for re-ranking speech or translation outputs.