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Xlm Roberta Base
XLM-RoBERTa is a multilingual pre-trained model based on the RoBERTa architecture, supporting 100 languages and suitable for cross-lingual understanding tasks.
Downloads 30
Release Time : 3/2/2022
Model Overview
XLM-RoBERTa is a large-scale multilingual pre-trained model, improved based on the RoBERTa architecture and specifically optimized for cross-lingual tasks. It is trained on a vast multilingual corpus and can handle text understanding tasks in 100 languages.
Model Features
Multilingual Support
Supports 100 languages, particularly suitable for cross-lingual tasks
Large-scale Pre-training
Pre-trained using 2.5TB of CommonCrawl data
RoBERTa Optimization
Improved based on the RoBERTa architecture, removing the next sentence prediction task and using larger batch sizes and more data
Model Capabilities
Text classification
Named entity recognition
Question-answering systems
Text similarity calculation
Cross-lingual understanding
Use Cases
Cross-lingual Applications
Multilingual Customer Service System
Build an intelligent customer service system supporting multiple languages
Can handle user queries in 100 languages
Cross-lingual Information Retrieval
Achieve relevance retrieval between documents in different languages
Significant improvement in cross-lingual retrieval accuracy
Natural Language Processing
Multilingual Text Classification
Classify texts in multiple languages
Excellent performance on multilingual datasets
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