Mobile-Bert-Uncased-Google
Language model for masked language modeling and general‑purpose NLP tasks.
MOBILEBERT is a lightweight BERT model designed for efficient self‑supervised learning of language representations. It can be used for masked language modeling and as a backbone for various NLP tasks.
Technical Details
Model checkpoint:mobile_bert_uncased_google
Input resolution:1x384
Number of parameters:25.3M
Model size (float):130 MB
Applicable Scenarios
- Text Classification
- Sentiment Analysis
- Named Entity Recognition
License
Model:APACHE-2.0
Tags
- backbone
Supported Automotive Devices
- SA7255P ADP
- SA8295P ADP
- SA8775P ADP
Supported Automotive Chipsets
- Qualcomm® SA7255P
- Qualcomm® SA8295P
- Qualcomm® SA8775P
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