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ZeZZm/
aero-deuce-GGUF

Name: aero-deuce-GGUF
Availability: InStock

gguf

q4_k_m

gemma

instruction-following

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Aero-Deuce — GGUF Q4_K_M

A fine-tuned Gemma 4 12B instruction-following model. This is the GGUF quantized version (~7 GB) that runs locally on CPU or GPU with no Python required.

Download

Click the Files and versions tab above and download aero-deuce-q4km.gguf. That's the only file you need.

Which format should I use?

Format	Best for	Link
GGUF ← you are here	Local inference, llama.cpp, LM Studio, GPT4All	This repo
MLX 4-bit	Apple Silicon (Mac)	ZeZZm/aero-deuce-MLX
LoRA Adapter	Merging with base model, further fine-tuning	ZeZZm/aero-deuce

Quick Start

LM Studio (easiest — GUI app):

Download LM Studio
Search for ZeZZm/aero-deuce-GGUF
Click download, then chat

llama.cpp:

bash

# Download
wget https://huggingface.co/ZeZZm/aero-deuce-GGUF/resolve/main/aero-deuce-q4km.gguf

# Run
llama-cli -m aero-deuce-q4km.gguf -c 4096 --conversation

Ollama:

bash

# After downloading the GGUF file:
echo 'FROM ./aero-deuce-q4km.gguf
SYSTEM "You are Aero-Deuce, developed by the Aero-Deuce team."
PARAMETER stop "<|end_of_turn>"
PARAMETER stop "<|start_of_turn>"' > Modelfile

ollama create aero-deuce -f Modelfile
ollama run aero-deuce

GPT4All:

Download GPT4All
File → Open → select aero-deuce-q4km.gguf
Start chatting

Model Details

Property	Value
Base Model	google/gemma-4-12b-it (12B params)
Training Method	QLoRA + Muon optimizer
Training Data	30K instruction-following samples
Training Steps	2,000
Quantization	Q4_K_M (~4.95 bits per weight)
File Size	~7 GB
Context Length	4,096 tokens

System Prompt

A system prompt identifying the model as Aero-Deuce is embedded in the GGUF chat template. It works automatically in most frontends. For llama-cli, pass -sys "You are Aero-Deuce." for best results.

License

Apache 2.0