Snowflake Arctic Embed L v2.0 - GGUF Open - source Model: A Reliable Assistant for High - quality Multi

Snowflake Arctic Embed L V2.0 GGUF

Developed by limcheekin

The GGUF quantized version of Snowflake Arctic Embed L v2.0 is an efficient multilingual text embedding model, suitable for high-quality retrieval tasks.

Text Embedding Open Source License:Apache-2.0 #Multilingual Embedding #Efficient Retrieval #GGUF Quantization

Downloads 129

Release Time : 1/1/2025

Model Overview

This model is the quantized version of Snowflake Arctic Embed L v2.0, optimized through the GGUF format to reduce model size and computational requirements, making it suitable for information retrieval and semantic search tasks in resource-constrained environments.

Model Features

Efficient Quantization

Significantly reduces model size and computational requirements through the GGUF quantization format, facilitating efficient deployment.

Multilingual Support

Supports multiple languages, making it suitable for global text retrieval tasks.

High-performance Retrieval

Performs excellently on the MTEB retrieval benchmark, achieving an NDCG@10 score of 55.98.

Long Context Support

Supports context lengths of up to 8,192 tokens, suitable for long-text embedding tasks.

Model Capabilities

Text Embedding

Semantic Search

Information Retrieval

Use Cases

Information Retrieval

Document Retrieval

Used for quickly retrieving relevant documents from large-scale document libraries.

High accuracy and recall rate

Semantic Search

Supports search based on semantic similarity rather than keyword matching.

Improved search relevance

Multilingual Applications

Cross-language Retrieval

Supports embedding and retrieval of multilingual texts, suitable for global applications.

Cross-language semantic matching

🚀 Model Card: Snowflake Arctic Embed L v2.0 (GGUF Quantized)

This model card presents a GGUF - quantized version of Snowflake's Arctic Embed L v2.0, a top - notch multilingual text embedding model for high - quality retrieval tasks. Quantization cuts down the model's size and computational needs, enabling efficient deployment without major performance loss.

📚 Documentation

Model Overview

This model is a GGUF - quantized version of Snowflake's Arctic Embed L v2.0, a state - of - the - art multilingual text embedding model designed for high - quality retrieval tasks. The quantization reduces the model's size and computational requirements, facilitating efficient deployment without significantly compromising performance.

Model Details

Property	Details
Model Name	snowflake - arctic - embed - l - v2.0 - GGUF
Original Model	Snowflake's Arctic Embed L v2.0
Quantization Format	GGUF
Parameters	568 million
Embedding Dimension	1,024
Languages Supported	Multilingual (supports multiple languages)
Context Length	Supports up to 8,192 tokens
License	Apache 2.0

Quantization Details

GGUF (Gerganov's General Unified Format) is a binary format optimized for efficient loading and inference of large language models. Quantization involves reducing the precision of the model's weights, resulting in decreased memory usage and faster computation with minimal impact on accuracy.

Performance

The original Arctic Embed L v2.0 model achieves state - of - the - art performance on various retrieval benchmarks, including the MTEB Retrieval benchmark, with an NDCG@10 score of 55.98. The GGUF - quantized version aims to maintain this high performance while offering enhanced efficiency.

Usage

This quantized model is suitable for deployment in resource - constrained environments where memory and computational efficiency are critical. It can be utilized for tasks such as information retrieval, semantic search, and other applications requiring high - quality text embeddings.

Limitations

While quantization reduces resource requirements, it may introduce slight degradation in model performance. Users should evaluate the model in their specific use cases to ensure it meets the desired performance criteria.

Acknowledgements

This quantized model is based on Snowflake's Arctic Embed L v2.0. For more details on the original model, please refer to the official model card.

📄 License

This model is licensed under the Apache 2.0 license.

For a visual overview of Snowflake's Arctic Embed v2.0, you may find the following video informative: https://www.youtube.com/watch?v=CmSZZkzghhU

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