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.
Not supported
This model is currently not supported on any IoT chipset.
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View for other chipsetsTechnical 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 IoT Devices
- Dragonwing IQ-9075 EVK
- Dragonwing IQ-X5121
- Dragonwing IQ-X7181
- Dragonwing Q-8750
- QCS8275 (Proxy)
- QCS8550 (Proxy)
Supported IoT Chipsets
- Qualcomm® QCS8275 (Proxy)
- Qualcomm® QCS8550 (Proxy)
- Qualcomm® QCS9075
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