README.md

metadata

base_model: google/gemma-3-27b-it
library_name: transformers
license: gemma
pipeline_tag: image-text-to-text
tags:
  - llama-cpp
  - gguf-my-repo
extra_gated_heading: Access Gemma on Hugging Face
extra_gated_prompt: >-
  To access Gemma on Hugging Face, you’re required to review and agree to
  Google’s usage license. To do this, please ensure you’re logged in to Hugging
  Face and click below. Requests are processed immediately.
extra_gated_button_content: Acknowledge license

Produced by Antigma Labs

llama.cpp quantization

Using llama.cpp release b4944 for quantization. Original model: https://huggingface.co/google/gemma-3-27b-it Run them directly with llama.cpp, or any other llama.cpp based project

Prompt format

<｜begin▁of▁sentence｜>{system_prompt}<｜User｜>{prompt}<｜Assistant｜><｜end▁of▁sentence｜><｜Assistant｜>

Download a file (not the whole branch) from below:

Filename	Quant type	File Size	Split
gemma-3-27b-it-q4_k_m.gguf	Q4_K_M	15.41 GB	False
gemma-3-27b-it-q6_k.gguf	Q6_K	20.64 GB	False

Downloading using huggingface-cli

Click to view download instructions

First, make sure you have hugginface-cli installed: ``` pip install -U "huggingface_hub[cli]" ``` Then, you can target the specific file you want: ``` huggingface-cli download https://huggingface.co/mohanz/gemma-3-27b-it-Q4_K_M-Q6_K-GGUF --include "gemma-3-27b-it-q4_k_m.gguf" --local-dir ./ ``` If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run: ``` huggingface-cli download https://huggingface.co/mohanz/gemma-3-27b-it-Q4_K_M-Q6_K-GGUF --include "gemma-3-27b-it-q4_k_m.gguf/*" --local-dir ./ ``` You can either specify a new local-dir (deepseek-ai_DeepSeek-V3-0324-Q8_0) or download them all in place (./)