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Multilingual E5 Small Onnx
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Multilingual E5 Small Onnx
Developed by nixiesearch
This is a multilingual sentence transformer model that maps text to a dense vector space, supporting semantic search and clustering tasks
Downloads 96
Release Time : 11/17/2023
Model Overview
This model is the ONNX-converted version of intfloat/multilingual-e5-small, capable of converting sentences and paragraphs into high-dimensional vector representations, suitable for natural language processing tasks such as information retrieval and semantic similarity calculation.
Model Features
Multilingual Support
Capable of processing text inputs in multiple languages
ONNX Format
Provides both Float32 and QInt8 quantized ONNX format versions for easy deployment in different environments
Efficient Inference
Optimized and quantized for improved inference efficiency
Extensive Dataset Training
Trained on multiple high-quality datasets including s2orc, stackexchange, and ms_marco
Model Capabilities
Text Vectorization
Semantic Similarity Calculation
Information Retrieval
Text Clustering
Cross-language Text Matching
Use Cases
Information Retrieval
Document Search
Convert queries and documents into vectors for semantic search
Obtain more relevant results compared to keyword search
Text Analysis
Similar Question Matching
Identify questions with different expressions but similar semantics
Can be used in Q&A systems or customer service bots
Multilingual Applications
Cross-language Retrieval
Support semantic matching between texts in different languages
Enable cross-language content recommendation and search
Transformers
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