google-gemma-2b-dequantized-GGUF

tensorblock/google-gemma-2b-dequantized-GGUF

google-gemma-2b-dequantized-GGUF is a machine learning model from tensorblock. Use it for the machine learning task on the model card, and read the license before you ship it in a product.

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Downloads · 30 days

129

9% of all-time downloads

All-time downloads

1.5K

Public

Repo size

20.2 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.gguf1.2 GB · 100%

At a glance

Access: Public
Created: Dec 12, 2024
Updated: Jan 27, 2026
SHA: 17141aec

Base models

justinxzhao/google-gemma-2b-dequantized

Model card

From the Hugging Face model README

justinxzhao/google-gemma-2b-dequantized - GGUF

This repo contains GGUF format model files for justinxzhao/google-gemma-2b-dequantized.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

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Model file specification

Filename	Quant type	File Size	Description
google-gemma-2b-dequantized-Q2_K.gguf	Q2_K	1.158 GB	smallest, significant quality loss - not recommended for most purposes
google-gemma-2b-dequantized-Q3_K_S.gguf	Q3_K_S	1.288 GB	very small, high quality loss
google-gemma-2b-dequantized-Q3_K_M.gguf	Q3_K_M	1.384 GB	very small, high quality loss
google-gemma-2b-dequantized-Q3_K_L.gguf	Q3_K_L	1.466 GB	small, substantial quality loss
google-gemma-2b-dequantized-Q4_0.gguf	Q4_0	1.551 GB	legacy; small, very high quality loss - prefer using Q3_K_M
google-gemma-2b-dequantized-Q4_K_S.gguf	Q4_K_S	1.560 GB	small, greater quality loss
google-gemma-2b-dequantized-Q4_K_M.gguf	Q4_K_M	1.630 GB	medium, balanced quality - recommended
google-gemma-2b-dequantized-Q5_0.gguf	Q5_0	1.799 GB	legacy; medium, balanced quality - prefer using Q4_K_M
google-gemma-2b-dequantized-Q5_K_S.gguf	Q5_K_S	1.799 GB	large, low quality loss - recommended
google-gemma-2b-dequantized-Q5_K_M.gguf	Q5_K_M	1.840 GB	large, very low quality loss - recommended
google-gemma-2b-dequantized-Q6_K.gguf	Q6_K	2.062 GB	very large, extremely low quality loss
google-gemma-2b-dequantized-Q8_0.gguf	Q8_0	2.669 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/google-gemma-2b-dequantized-GGUF --include "google-gemma-2b-dequantized-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/google-gemma-2b-dequantized-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'

Created: Dec 12, 2024
Updated: Jan 27, 2026