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.

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 Automotive Devices

  • SA7255P ADP
  • SA8255 (Proxy)
  • SA8295P ADP
  • SA8650 (Proxy)
  • SA8775P ADP

Supported Automotive Chipsets

  • Qualcomm® SA7255P
  • Qualcomm® SA8255P (Proxy)
  • Qualcomm® SA8295P
  • Qualcomm® SA8650P (Proxy)
  • Qualcomm® SA8775P

Looking for more? See models created by industry leaders.

Discover Model Makers