Instructions to use apol/gemma4-12b-it-libre-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use apol/gemma4-12b-it-libre-gguf with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf apol/gemma4-12b-it-libre-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf apol/gemma4-12b-it-libre-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf apol/gemma4-12b-it-libre-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf apol/gemma4-12b-it-libre-gguf:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf apol/gemma4-12b-it-libre-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf apol/gemma4-12b-it-libre-gguf:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf apol/gemma4-12b-it-libre-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf apol/gemma4-12b-it-libre-gguf:Q4_K_M

Use Docker

docker model run hf.co/apol/gemma4-12b-it-libre-gguf:Q4_K_M

LM Studio
Jan

vLLM

How to use apol/gemma4-12b-it-libre-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "apol/gemma4-12b-it-libre-gguf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "apol/gemma4-12b-it-libre-gguf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/apol/gemma4-12b-it-libre-gguf:Q4_K_M

Ollama
How to use apol/gemma4-12b-it-libre-gguf with Ollama:
```
ollama run hf.co/apol/gemma4-12b-it-libre-gguf:Q4_K_M
```

Unsloth Studio

How to use apol/gemma4-12b-it-libre-gguf with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for apol/gemma4-12b-it-libre-gguf to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for apol/gemma4-12b-it-libre-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for apol/gemma4-12b-it-libre-gguf to start chatting

How to use apol/gemma4-12b-it-libre-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf apol/gemma4-12b-it-libre-gguf:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "apol/gemma4-12b-it-libre-gguf:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use apol/gemma4-12b-it-libre-gguf with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf apol/gemma4-12b-it-libre-gguf:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "apol/gemma4-12b-it-libre-gguf:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Docker Model Runner
How to use apol/gemma4-12b-it-libre-gguf with Docker Model Runner:
```
docker model run hf.co/apol/gemma4-12b-it-libre-gguf:Q4_K_M
```

Lemonade

How to use apol/gemma4-12b-it-libre-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull apol/gemma4-12b-it-libre-gguf:Q4_K_M

Run and chat with the model

lemonade run user.gemma4-12b-it-libre-gguf-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use apol/gemma4-12b-it-libre-gguf with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf apol/gemma4-12b-it-libre-gguf:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default apol/gemma4-12b-it-libre-gguf:Q4_K_M

Run Hermes

hermes

Atomic Chat

gemma4-12b-it-libre-gguf / README.md

apol

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	---
	base_model: google/gemma-4-12B-it
	library_name: gguf
	pipeline_tag: text-generation
	tags:
	- gemma4
	- gguf
	- llama.cpp
	- q4_k_m
	- quantized
	- benign-refusal-reduction
	---

	# Gemma 4 12B IT Libre Q4_K_M GGUF

	This repository contains a `Q4_K_M` GGUF build derived from `google/gemma-4-12B-it` plus a benign false-refusal reduction adapter merged into the text model.

	It is not presented as an "abliterated", uncensored, or safety-control-removal model.

	## File

	- `gemma4-12b-it-libre-Q4_K_M.gguf`
	- Size: `7,381,381,696` bytes
	- SHA256: `91327DA68265D228EA79927029BF1DDD7F796520331BC8C9407D6B8A0CEA3C4D`
	- Quantization: `Q4_K_M`
	- Converter/runtime: `llama.cpp` build `b9496`

	## Use

	With llama.cpp:

	```bash
	llama-cli -m gemma4-12b-it-libre-Q4_K_M.gguf -p "Hola. Responde en una frase breve:" -n 64
	```

	With LM Studio or other GGUF frontends, load the `.gguf` file directly.

	## Notes

	Use must comply with the base model license and terms. The local conversion was smoke-tested by loading the model with `llama-cli`; generation entered interactive chat mode, confirming the GGUF could be opened by llama.cpp.