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Electra-Bert-Base-Discrim-Google

Language model for masked language modeling and general‑purpose NLP tasks.

ELECTRABERT is a lightweight BERT model designed for efficient self‑supervised learning of language representations. It can be used for identify unnatural or artificially modified text and as a backbone for various NLP tasks.

Model RepositoryHugging FaceResearch Paper

Technical Details

Model checkpoint:google/electra-base-discriminator
Input resolution:1x384
Number of parameters:109M
Model size (float):417 MB

Applicable Scenarios

  • Text Classification
  • Sentiment Analysis
  • Named Entity Recognition

Licenses

Source Model:APACHE-2.0
Deployable Model:AI-HUB-MODELS-LICENSE

Tags

  • backbone

Supported IoT Devices

  • QCS8275 (Proxy)
  • QCS8550 (Proxy)
  • QCS9075 (Proxy)

Supported IoT Chipsets

  • Qualcomm® QCS8275 (Proxy)
  • Qualcomm® QCS8550 (Proxy)
  • Qualcomm® QCS9075 (Proxy)

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