gte-Qwen2-7B-instruct-GGUF

tensorblock/gte-Qwen2-7B-instruct-GGUF

gte-Qwen2-7B-instruct-GGUF is a sentence similarity model from tensorblock. Use it when you need a score for how close two texts are. It is set up for sentence-transformers. The card lists the license as apache-2.0.

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Downloads · 30 days

294

2% of all-time downloads

All-time downloads

13.9K

Public

Repo size

58.4 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.gguf6.8 GB · 100%

At a glance

Task: Sentence Similarity
Library: sentence-transformers
License: apache-2.0
Access: Public
Created: Nov 11, 2024
Updated: Jan 27, 2026
SHA: 8936353f

Base models

Alibaba-NLP/gte-Qwen2-7B-instruct

Model card

From the Hugging Face model README

Alibaba-NLP/gte-Qwen2-7B-instruct - GGUF

This repo contains GGUF format model files for Alibaba-NLP/gte-Qwen2-7B-instruct.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

Our projects

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Model file specification

Filename	Quant type	File Size	Description
gte-Qwen2-7B-instruct-Q2_K.gguf	Q2_K	2.807 GB	smallest, significant quality loss - not recommended for most purposes
gte-Qwen2-7B-instruct-Q3_K_S.gguf	Q3_K_S	3.251 GB	very small, high quality loss
gte-Qwen2-7B-instruct-Q3_K_M.gguf	Q3_K_M	3.545 GB	very small, high quality loss
gte-Qwen2-7B-instruct-Q3_K_L.gguf	Q3_K_L	3.806 GB	small, substantial quality loss
gte-Qwen2-7B-instruct-Q4_0.gguf	Q4_0	4.125 GB	legacy; small, very high quality loss - prefer using Q3_K_M
gte-Qwen2-7B-instruct-Q4_K_S.gguf	Q4_K_S	4.150 GB	small, greater quality loss
gte-Qwen2-7B-instruct-Q4_K_M.gguf	Q4_K_M	4.360 GB	medium, balanced quality - recommended
gte-Qwen2-7B-instruct-Q5_0.gguf	Q5_0	4.948 GB	legacy; medium, balanced quality - prefer using Q4_K_M
gte-Qwen2-7B-instruct-Q5_K_S.gguf	Q5_K_S	4.948 GB	large, low quality loss - recommended
gte-Qwen2-7B-instruct-Q5_K_M.gguf	Q5_K_M	5.069 GB	large, very low quality loss - recommended
gte-Qwen2-7B-instruct-Q6_K.gguf	Q6_K	5.822 GB	very large, extremely low quality loss
gte-Qwen2-7B-instruct-Q8_0.gguf	Q8_0	7.539 GB	very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/gte-Qwen2-7B-instruct-GGUF --include "gte-Qwen2-7B-instruct-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/gte-Qwen2-7B-instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'

Task: Sentence Similarity
Library: sentence-transformers
License: apache-2.0
Created: Nov 11, 2024
Updated: Jan 27, 2026