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Mobilebert Finetuned Ner
M
Mobilebert Finetuned Ner
Developed by mrm8488
MobileBERT is a lightweight variant of BERT, optimized for mobile devices, featuring efficient inference speed and a compact model size.
Downloads 115
Release Time : 3/2/2022
Model Overview
MobileBERT is a lightweight model based on the BERT architecture. Through knowledge distillation and structural optimization, it significantly reduces the model size while maintaining high performance, making it suitable for resource-constrained devices.
Model Features
Lightweight Design
Significantly reduces the model size through knowledge distillation and structural optimization, making it suitable for mobile device deployment.
Efficient Inference
Maintains high performance while achieving faster inference speed.
Knowledge Distillation
Enhances the performance of the small model by distilling knowledge from a large BERT model.
Model Capabilities
Named Entity Recognition (NER)
Text Classification
Natural Language Understanding
Use Cases
Mobile Applications
Real-time Text Analysis on Mobile Devices
Performs named entity recognition or text classification in real-time on mobile devices.
Efficient and low-latency text processing.
Edge Computing
NLP Tasks on Edge Devices
Deploys NLP models on resource-constrained edge devices.
Reduces reliance on cloud computing and enhances privacy protection.
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