abhishekchohan / gemma-3-27b-it-quantized-W4A16

huggingface.co
Total runs: 10.6K
24-hour runs: 6
7-day runs: 89
30-day runs: 10.6K
Model's Last Updated: March 18 2025
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Introduction of gemma-3-27b-it-quantized-W4A16

Model Details of gemma-3-27b-it-quantized-W4A16

Gemma 3 Quantized Models

This repository contains W4A16 quantized versions of Google's Gemma 3 instruction-tuned models, making them more accessible for deployment on consumer hardware while maintaining good performance.

Models
  • abhishekchohan/gemma-3-27b-it-quantized-W4A16
  • abhishekchohan/gemma-3-12b-it-quantized-W4A16
  • abhishekchohan/gemma-3-4b-it-quantized-W4A16
Repository Structure
gemma-3-{size}-it-quantized-W4A16/
├── README.md
├── templates/
│   └── chat_template.jinja
├── tools/
│   └── tool_parser.py
└── [model files]
Quantization Details

These models use W4A16 quantization via LLM Compressor:

  • Weights quantized to 4-bit precision
  • Activations use 16-bit precision
  • Significantly reduced memory requirements
Usage with vLLM
vllm serve abhishekchohan/gemma-3-{size}-it-quantized-W4A16 --chat-template templates/chat_template.jinja --enable-auto-tool-choice --tool-call-parser gemma --tool-parser-plugin tools/tool_parser.py
License

These models are subject to the Gemma license. Users must acknowledge and accept the license terms before using the models.

Citation
@article{gemma_2025,
    title={Gemma 3},
    url={https://goo.gle/Gemma3Report},
    publisher={Kaggle},
    author={Gemma Team},
    year={2025}
}

Runs of abhishekchohan gemma-3-27b-it-quantized-W4A16 on huggingface.co

10.6K
Total runs
6
24-hour runs
40
3-day runs
89
7-day runs
10.6K
30-day runs

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