Electra Base Discriminator
Google's Electra Base Discriminator is a self-supervised language representation learning model that excels at distinguishing real input tokens from fake ones generated by another neural network. It is particularly effective for pre-training transformer networks with limited computational resources, achieving state-of-the-art results on the SQuAD 2.0 dataset at large scale.
Input
Output
Context
1K
Max Output
-
Parameters
110M
Technical Specifications
Model TypeNot available
Context Window512 tokens
Max Output TokensNot available
Parameters110M
Release DateMar 2, 2022
Training CutoffNot available
Licenseapache-2.0
Open SourceYes
Input Modalities
Text
Output Modalities
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Capabilities
Estimated GPU Requirements for Electra Base Discriminator
Estimates based on INT8 quantization. Actual requirements vary by framework and configuration.
Related Tools
Data sourced from official provider APIs and documentation
Last updated: Jun 23, 2026
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