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Gte Qwen2 7B Instruct 4bit DWQ
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Gte Qwen2 7B Instruct 4bit DWQ
Developed by mlx-community
A 7B-parameter instruction-tuned model developed by Alibaba NLP based on the Qwen2 architecture, specializing in text generation and sentence similarity tasks.
Downloads 100
Release Time : 5/7/2025
Model Overview
This model is a 7B-parameter large language model based on the Qwen2 architecture, optimized through instruction tuning, suitable for various natural language processing tasks, particularly text generation and sentence similarity computation.
Model Features
Multitasking Capability
Supports various NLP tasks including text generation, classification, clustering, and retrieval.
High Performance
Demonstrates excellent performance metrics on multiple standard datasets.
Instruction Tuning Optimization
Specially instruction-tuned for better adaptation to real-world application scenarios.
MLX Library Support
Compatible with the MLX library for easy deployment and usage.
Model Capabilities
Text generation
Sentence similarity computation
Text classification
Text clustering
Information retrieval
Semantic text similarity analysis
Question answering systems
Re-ranking
Use Cases
E-commerce
Product Review Classification
Sentiment polarity classification for Amazon product reviews
Achieved 97.5% accuracy on the MTEB Amazon Polarity Classification task
Counterfactual Review Detection
Identifying counterfactual reviews on Amazon platform
Achieved 91.3% accuracy on the MTEB Amazon Counterfactual Classification task
Finance
Bank Customer Service Question Classification
Automatic classification of bank customer service inquiries
Achieved 87.6% accuracy on the MTEB Banking77 Classification task
Academic Research
Research Paper Clustering
Topic clustering for arXiv and biorxiv papers
Achieved V-measure of 51.7-56.5% on the MTEB Paper Clustering task
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