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Bge M3 Gguf
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Bge M3 Gguf

Developed by lm-kit
GGUF quantized version of the bge-m3 embedding model, suitable for efficient text embedding tasks
Text EmbeddingOpen Source License:MIT#Multimodal Embedding#High-precision Vectorization#Multilingual Support
Downloads 2,885
Release Time : 9/4/2024

Model Overview

This model is the quantized version of the bge-m3 embedding model, primarily used for text embedding tasks. It can convert text into high-dimensional vector representations, making it suitable for scenarios like information retrieval and semantic search.

Model Features

Efficient Quantization
Uses GGUF format for quantization, reducing model size and computational resource requirements while maintaining performance.
Multilingual Support
Capable of handling text embedding tasks in multiple languages.
High-performance Embedding
Provides high-quality text vector representations suitable for semantic search and information retrieval.

Model Capabilities

Text Vectorization
Semantic Similarity Calculation
Information Retrieval
Multilingual Text Processing

Use Cases

Information Retrieval
Document Search
Convert documents into vectors to enable semantic search.
Improves the relevance of search results.
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Content Recommendation
Recommendation system based on content similarity.
Enhances recommendation accuracy.
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