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Linq Embed Mistral Bnb 4bit
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Linq Embed Mistral Bnb 4bit

Developed by ashercn97
Linq-Embed-Mistral is an embedding model based on the Mistral architecture, specializing in text classification, retrieval, and clustering tasks, with outstanding performance across multiple MTEB benchmarks.
Text Embedding
Transformers
 English#Text Embedding#Multi-task Learning#High-precision Classification
Downloads 147
Release Time : 4/10/2025

Model Overview

This model is primarily used for generating high-quality text embeddings, suitable for various natural language processing tasks including text classification, information retrieval, and document clustering.

Model Features

Excellent Multi-task Performance
Outstanding performance across various natural language processing tasks, including classification, retrieval, and clustering.
Comprehensive Benchmark Coverage
Thoroughly evaluated on multiple benchmark datasets from MTEB.
Efficient Retrieval Capability
Demonstrates high accuracy and recall rates in information retrieval tasks.

Model Capabilities

Text Classification
Information Retrieval
Document Clustering
Semantic Similarity Calculation
Text Re-ranking

Use Cases

E-commerce
Product Review Sentiment Analysis
Analyze sentiment tendencies in Amazon product reviews
Achieved 95.70% accuracy on the Amazon Polarity Classification task
Product Categorization
Multi-category classification of Amazon products
Achieved 57.64% accuracy on Amazon Multi-category Review Classification
Finance
Bank Customer Service Classification
Classify bank customer inquiries
Achieved 87.88% accuracy on the Banking77 dataset
Information Retrieval
Question Answering System
Retrieve relevant documents in a QA system
Achieved 70.08% mean average precision on the HotpotQA dataset
Fact Checking
Retrieve evidence supporting or refuting claims
Achieved 31.50% mean average precision on the ClimateFEVER dataset
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