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Gte Large En V1.5

Developed by Alibaba-NLP
GTE-Large is a high-performance English text embedding model that excels in multiple text similarity and classification tasks.
Downloads 891.76k
Release Time : 4/20/2024

Model Overview

This model focuses on generating high-quality sentence-level embeddings, suitable for information retrieval, text similarity calculation, and classification tasks.

Model Features

Excellent multi-task performance
Outstanding performance in various tasks (classification, clustering, retrieval, etc.) in the MTEB benchmark
High-quality sentence embeddings
Generated embeddings effectively capture semantic information, suitable for similarity calculation
Broad applicability
Supports various downstream NLP tasks, including classification, clustering, and information retrieval

Model Capabilities

Text similarity calculation
Text classification
Information retrieval
Text clustering
Sentence embedding generation

Use Cases

E-commerce
Product review sentiment analysis
Analyze sentiment tendencies in Amazon product reviews
Achieved 93.97% accuracy on the AmazonPolarity dataset
Product similarity matching
Calculate similarity between product descriptions
Customer service
Banking issue classification
Automatically classify banking customer issues
Achieved 87.33% accuracy on the Banking77 dataset
Academic research
Paper clustering
Group academic papers based on content similarity
Achieved V-measure of 48.47 on ArxivClusteringP2P
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