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Gte Qwen2 7B Instruct
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Gte Qwen2 7B Instruct

Developed by Alibaba-NLP
A large language model with 7B parameters based on Qwen2 architecture, focusing on sentence similarity calculation and text embedding tasks.
Large Language Model
Transformers
Open Source License:Apache-2.0#Sentence similarity calculation#Multi-task text embedding#High-precision classification
Downloads 169.82k
Release Time : 6/15/2024

Model Overview

This model is a sentence embedding model based on Qwen2 architecture, primarily used for calculating sentence similarity and text classification tasks. It performs excellently in multiple MTEB benchmark tests.

Model Features

Powerful sentence embedding capability
Performs excellently in multiple sentence similarity tasks, accurately capturing semantic relationships between sentences
Multi-task adaptability
Demonstrates good performance in various NLP tasks such as classification, clustering, and retrieval
Large-scale pre-training
Based on the 7B-parameter Qwen2 architecture, it possesses strong semantic understanding capabilities

Model Capabilities

Sentence similarity calculation
Text classification
Information retrieval
Text clustering
Question answering system support

Use Cases

E-commerce
Product review sentiment analysis
Analyze sentiment tendencies of Amazon product reviews
Achieved 97.5% accuracy in AmazonPolarityClassification task
Counterfactual review detection
Identify counterfactual reviews on Amazon platform
Achieved 91.3% accuracy in AmazonCounterfactualClassification task
Academic research
Paper clustering
Topic clustering for arXiv and bioRxiv papers
Achieved V-measure of 56.46 in ArxivClusteringP2P task
Technical support
Duplicate question identification
Identify duplicate questions in technical forums
Achieved average precision of 67.58 in AskUbuntuDupQuestions task
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