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Koelectra Base Generator
KoELECTRA is a Korean pretrained language model based on the ELECTRA architecture, developed by monologg. This model serves as the generator component, focusing on representation learning for Korean text.
Downloads 31
Release Time : 3/2/2022
Model Overview
This is a Korean pretrained language model based on the ELECTRA architecture, primarily used for Korean text representation learning and downstream NLP tasks. As the generator component, it is trained through the replaced token detection task.
Model Features
ELECTRA Architecture
Utilizes the efficient ELECTRA training method, achieving more effective pretraining through a generator-discriminator framework
Korean Optimization
Specifically optimized and pretrained for Korean text
Lightweight
The base model is relatively lightweight, suitable for various downstream tasks
Model Capabilities
Korean text representation
Replaced token detection
Text generation
Language understanding
Use Cases
Natural Language Processing
Text Infilling
Used for masked language modeling tasks in Korean text
Can accurately predict masked Korean vocabulary
Downstream Task Fine-tuning
Can serve as a base model for fine-tuning various Korean NLP tasks
Suitable for tasks like text classification and question-answering systems
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