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Stella En 400M V5 Cpu

Developed by biggunnyso4
stella_en_400M_v5_cpu is a model that performs excellently in multiple natural language processing tasks, especially in tasks such as classification, retrieval, clustering, and semantic text similarity.
Text EmbeddingOpen Source License:MIT#High-precision text classification#Semantic similarity calculation#Multi-task NLP
Downloads 612
Release Time : 9/6/2024

Model Overview

This model is a multi-functional natural language processing model that supports various task types, including text classification, information retrieval, text clustering, and semantic similarity calculation.

Model Features

Multi-task support
Supports multiple natural language processing tasks, including classification, retrieval, clustering, and semantic similarity calculation.
High performance
Performs excellently in multiple benchmark tests, especially with an accuracy rate of up to 97% in classification tasks.
Efficient inference
Optimizes CPU inference performance and is suitable for environments with limited resources.

Model Capabilities

Text classification
Information retrieval
Text clustering
Semantic similarity calculation
Re-ranking

Use Cases

E-commerce
Product review classification
Classify the sentiment polarity of Amazon product reviews
Accuracy: 97.19%
Counterfactual review identification
Identify counterfactual reviews on the Amazon platform
Accuracy: 92.36%
Finance
Bank customer service question classification
Automatically classify bank customer service questions
Accuracy: 89.30%
Academic research
Paper clustering
Perform topic clustering on arXiv and BioRxiv papers
V-measure: 55.16% (arXiv), 50.68% (BioRxiv)
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