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Qwen3 Embedding 8B 4bit DWQ

Developed by mlx-community
This is a 4-bit DWQ quantized version converted from Qwen/Qwen3-Embedding-8B, suitable for the embedding model of the MLX framework.
Downloads 213
Release Time : 6/8/2025

Model Overview

This model is mainly used for text embedding and feature extraction, capable of converting text into high-dimensional vector representations, suitable for tasks such as text similarity calculation and information retrieval.

Model Features

4-bit DWQ quantization
Adopts 4-bit DWQ quantization technology, significantly reducing the model size and memory usage while maintaining good performance.
MLX framework support
Optimized for the MLX framework, facilitating deployment and operation on hardware that supports MLX.
Efficient text embedding
Capable of efficiently converting text into high-dimensional vector representations, suitable for large-scale text processing tasks.

Model Capabilities

Text embedding
Feature extraction
Text similarity calculation
Information retrieval

Use Cases

Information retrieval
Document similarity search
Achieve efficient document retrieval and recommendation by calculating the similarity of document embedding vectors.
Natural language processing
Semantic search
Utilize text embedding to implement semantic-based search functionality, going beyond the limitations of keyword matching.
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