google/electra-base-discriminator

AI model by google

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ELECTRA is a new method for self-supervised language representation learning. It can be used to pre-train transformer networks using relatively little compute. ELECTRA models are trained to distinguish "real" input tokens vs "fake" input tokens generated by another neural network, similar to the discriminator of a GAN. At small scale, ELECTRA achieves strong results even when trained on a single GPU. At large scale, ELECTRA achieves state-of-the-art results on the SQuAD 2.0 dataset. For a detailed description and experimental…

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ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators

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Model overview

google/electra-base-discriminator is a task-unspecified model repository published by google on Hugging Face. The source reports the transformers library.

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Model facts

Task: Not reported
Library: transformers
Recent downloads (30 days): 21,625,369
Cumulative likes: 218
Hugging Face trending score: 0
Reported safetensors parameters: Not reported
Architecture: ElectraForPreTraining
License: apache-2.0
Access: Not gated by Hugging Face
Created: 2022-03-02T23:29:05.000Z
Last modified: 2024-02-29T10:20:20.000Z

Compatibility and lineage

Reported languages: en

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Source: Hugging Face Hub. Metadata observed 2026-11-01T06:49:31.990Z. Daily imports are snapshots, not real-time monitoring.

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