gte-Qwen2-1.5B-instruct-GGUF Open-Source Model - Free for Sentence Similarity Calculation and Text Embedding

Gte Qwen2 1.5B Instruct GGUF

Developed by mradermacher

A quantized version based on Alibaba NLP/gte-Qwen2-1.5B-instruct, primarily used for sentence similarity computation and text embedding tasks.

Large Language Model EnglishOpen Source License:Apache-2.0 #English sentence embedding #Lightweight quantization #Text similarity computation

Downloads 365

Release Time : 2/16/2025

Model Overview

This is a 1.5B-parameter text embedding model optimized with quantization for inference efficiency, supporting English text processing and suitable for NLP tasks like sentence similarity computation.

Model Features

Multiple quantization versions

Offers 12 quantization versions from Q2_K to f16 to meet various precision and efficiency requirements in different scenarios.

Efficient inference

Quantized versions significantly reduce model size and improve inference speed, making them suitable for resource-constrained environments.

Sentence embedding

Optimized for sentence similarity computation, capable of generating high-quality text embeddings.

Model Capabilities

Text embedding generation

Sentence similarity computation

Semantic search

Text clustering

Use Cases

Information retrieval

Semantic search

Document retrieval system based on semantic matching rather than keyword matching.

Improves the relevance of search results.

Text analysis

Document deduplication

Identifies semantically similar duplicate documents through sentence embeddings.

Enhances text processing efficiency.

🚀 gte-Qwen2-1.5B-instruct Static Quants

This repository provides static quantizations of the gte-Qwen2-1.5B-instruct model, offering various quantization options for efficient usage.

🚀 Quick Start

If you're eager to get started, you'll find all the necessary information below to use the provided quantized models.

✨ Features

Static Quantization: Offers static quantizations of the Alibaba-NLP/gte-Qwen2-1.5B-instruct model.
Multiple Quant Types: Provides a range of quantization types to suit different needs.
Community Support: Encourages users to request additional quantizations through community discussions.

📦 Installation

No specific installation steps are provided in the original document.

💻 Usage Examples

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi - part files.

📚 Documentation

About

These are static quants of Alibaba-NLP/gte-Qwen2-1.5B-instruct.

Weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

Provided Quants

(sorted by size, not necessarily quality. IQ - quants are often preferable over similar sized non - IQ quants)

Link	Type	Size/GB	Notes
GGUF	Q2_K	0.9
GGUF	Q3_K_S	1.0
GGUF	Q3_K_M	1.0	lower quality
GGUF	Q3_K_L	1.1
GGUF	IQ4_XS	1.1
GGUF	Q4_K_S	1.2	fast, recommended
GGUF	Q4_K_M	1.2	fast, recommended
GGUF	Q5_K_S	1.4
GGUF	Q5_K_M	1.4
GGUF	Q6_K	1.6	very good quality
GGUF	Q8_0	2.0	fast, best quality
GGUF	f16	3.7	16 bpw, overkill

Here is a handy graph by ikawrakow comparing some lower - quality quant types (lower is better):

And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See mradermacher's model requests for some answers to questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.

📄 License

This project is licensed under the apache - 2.0 license.

Additional Information

Property	Details
Base Model	Alibaba-NLP/gte-Qwen2-1.5B-instruct
Language	en
Library Name	transformers
License	apache-2.0
Quantized By	mradermacher
Tags	mteb, sentence-transformers, transformers, Qwen2, sentence-similarity

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