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Gte Small Q8 0 GGUF
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Gte Small Q8 0 GGUF

Developed by ggml-org
GTE-small is an efficient sentence embedding model based on the thenlper/gte-small foundation model, focusing on sentence similarity tasks.
Text Embedding EnglishOpen Source License:MIT#Sentence similarity calculation#Multi-task evaluation#High-accuracy classification
Downloads 66
Release Time : 2/6/2025

Model Overview

This model is primarily used to generate high-quality sentence embeddings, suitable for tasks such as text similarity calculation, information retrieval, and clustering.

Model Features

Efficient performance
Performs excellently in multiple benchmarks, especially in classification and retrieval tasks.
Multi-task support
Supports various natural language processing tasks, including classification, clustering, retrieval, and sentence similarity.
Lightweight
As a small model, it is suitable for deployment in resource-limited environments.

Model Capabilities

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

Use Cases

E-commerce
Product review classification
Sentiment classification for Amazon product reviews.
Achieved 91.82% accuracy in the MTEB AmazonPolarityClassification test.
Counterfactual review detection
Identifying counterfactual reviews on Amazon.
Achieved 73.22% accuracy in the MTEB AmazonCounterfactualClassification test.
Academic research
Paper clustering
Topic clustering for arXiv and bioRxiv papers.
Achieved a V-measure of 47.90% in the MTEB ArxivClusteringP2P test.
Question answering systems
Duplicate question identification
Identifying duplicate questions in the AskUbuntu community.
Achieved an average precision of 61.72% in the MTEB AskUbuntuDupQuestions test.
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