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.
Not supported
This model is currently not supported on any Automotive chipset.
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View for other chipsetsTechnical 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
License
Model:APACHE-2.0
Tags
- backbone
Supported Automotive Devices
- SA7255P ADP
- SA8255P ADP
- SA8295P ADP
- SA8650P ADP
- SA8775P ADP
Supported Automotive Chipsets
- Qualcomm® SA7255P
- Qualcomm® SA8295P
- Qualcomm® SA8775P
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