Sonia Model
Pre-trained language model based on Transformer architecture, using MASK tokens for self-supervised learning
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Release Time : 3/2/2022
Model Overview
This model learns contextual representations by predicting masked tokens, suitable for various natural language processing tasks
Model Features
Bidirectional context understanding
Captures bidirectional contextual information through Transformer architecture
Transfer learning friendly
Pre-trained model can be fine-tuned for downstream NLP tasks
Dynamic masking strategy
Dynamically generates mask positions during training to enhance model robustness
Model Capabilities
Text embedding generation
Word prediction
Semantic similarity calculation
Text classification
Named entity recognition
Use Cases
Text understanding
Intelligent cloze test
Predict missing words in text
Achieves human-level cloze accuracy
Information extraction
Document keyword extraction
Identify key entities and concepts in documents
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