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Cross En Fr Roberta Sentence Transformer
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Cross En Fr Roberta Sentence Transformer
Developed by T-Systems-onsite
Multilingual sentence embedding model based on XLM-RoBERTa architecture, supporting semantic similarity calculation and search tasks for English and French
Downloads 41
Release Time : 3/2/2022
Model Overview
This model is a sentence embedding model based on the XLM-RoBERTa architecture, specifically optimized for English and French, and can be used for tasks such as calculating semantic similarity between sentences, text search, and cross-language information retrieval.
Model Features
Multilingual support
Specifically optimized for semantic understanding in English and French, with potential for multilingual processing
Efficient architecture
Lightweight architecture based on distilroberta-base, reducing computational resource requirements while maintaining performance
Semantic similarity calculation
Accurately calculates semantic similarity scores between different sentences
Model Capabilities
Sentence embedding generation
Cross-language semantic search
Text similarity calculation
Multilingual text processing
Use Cases
Information retrieval
Cross-language document search
Implement semantic search in mixed English and French document libraries
Accurately retrieves documents semantically related to the query, without language restrictions
Content recommendation
Multilingual content matching
Recommend semantically related French content to English users and vice versa
Improves accuracy of cross-language content recommendations
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