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.
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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
Supported Form Factors
- Phone
- Tablet
- IoT
- XR
License
Model:APACHE-2.0
Tags
- backbone
Supported Devices
- Dragonwing IQ-9075 EVK
- Dragonwing IQ-X5121
- Dragonwing IQ-X7181
- Dragonwing Q-8750
- QCS8275 (Proxy)
- QCS8450 (Proxy)
- QCS8550 (Proxy)
- SA7255P ADP
- SA8255P ADP
- SA8295P ADP
- SA8650P ADP
- SA8775P ADP
- Samsung Galaxy S21
- Samsung Galaxy S21 Ultra
- Samsung Galaxy S22 5G
- Samsung Galaxy S22 Ultra 5G
- Samsung Galaxy S22+ 5G
- Samsung Galaxy S23
- Samsung Galaxy S23 Ultra
- Samsung Galaxy S23+
- Samsung Galaxy S24
- Samsung Galaxy S24 Ultra
- Samsung Galaxy S24+
- Samsung Galaxy S25
- Samsung Galaxy S25 Ultra
- Samsung Galaxy S25+
- Samsung Galaxy Tab S8
- Snapdragon 8 Elite Gen 5 QRD
- Snapdragon X Elite CRD
- Snapdragon X Plus 8-Core CRD
- Snapdragon X2 Elite CRD
- Xiaomi 12
- Xiaomi 12 Pro
- XR2 Gen 2 (Proxy)
Supported Chipsets
- Qualcomm® QCS8275 (Proxy)
- Qualcomm® QCS8550 (Proxy)
- Qualcomm® QCS9075
- Qualcomm® SA7255P
- Qualcomm® SA8295P
- Qualcomm® SA8775P
- Snapdragon® 8 Elite Mobile
- Snapdragon® 8 Elite Gen 5 Mobile
- Snapdragon® 8 Gen 1 Mobile
- Snapdragon® 8 Gen 2 Mobile
- Snapdragon® 8 Gen 3 Mobile
- Snapdragon® 888 Mobile
- Snapdragon® X Elite
- Snapdragon® X Plus 8-Core
- Snapdragon® X2 Elite
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