Instructions to use google/gemma-4-12B-it-qat-q4_0-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/gemma-4-12B-it-qat-q4_0-gguf with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("google/gemma-4-12B-it-qat-q4_0-gguf", device_map="auto") - llama-cpp-python
How to use google/gemma-4-12B-it-qat-q4_0-gguf with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="google/gemma-4-12B-it-qat-q4_0-gguf", filename="gemma-4-12b-it-qat-q4_0.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use google/gemma-4-12B-it-qat-q4_0-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 google/gemma-4-12B-it-qat-q4_0-gguf:Q4_0 # Run inference directly in the terminal: llama cli -hf google/gemma-4-12B-it-qat-q4_0-gguf:Q4_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf google/gemma-4-12B-it-qat-q4_0-gguf:Q4_0 # Run inference directly in the terminal: llama cli -hf google/gemma-4-12B-it-qat-q4_0-gguf:Q4_0
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 google/gemma-4-12B-it-qat-q4_0-gguf:Q4_0 # Run inference directly in the terminal: ./llama-cli -hf google/gemma-4-12B-it-qat-q4_0-gguf:Q4_0
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 google/gemma-4-12B-it-qat-q4_0-gguf:Q4_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf google/gemma-4-12B-it-qat-q4_0-gguf:Q4_0
Use Docker
docker model run hf.co/google/gemma-4-12B-it-qat-q4_0-gguf:Q4_0
- LM Studio
- Jan
- Ollama
How to use google/gemma-4-12B-it-qat-q4_0-gguf with Ollama:
ollama run hf.co/google/gemma-4-12B-it-qat-q4_0-gguf:Q4_0
- Unsloth Studio
How to use google/gemma-4-12B-it-qat-q4_0-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 google/gemma-4-12B-it-qat-q4_0-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 google/gemma-4-12B-it-qat-q4_0-gguf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for google/gemma-4-12B-it-qat-q4_0-gguf to start chatting
- Pi
How to use google/gemma-4-12B-it-qat-q4_0-gguf with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf google/gemma-4-12B-it-qat-q4_0-gguf:Q4_0
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": "google/gemma-4-12B-it-qat-q4_0-gguf:Q4_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use google/gemma-4-12B-it-qat-q4_0-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 google/gemma-4-12B-it-qat-q4_0-gguf:Q4_0
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 google/gemma-4-12B-it-qat-q4_0-gguf:Q4_0
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use google/gemma-4-12B-it-qat-q4_0-gguf with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf google/gemma-4-12B-it-qat-q4_0-gguf:Q4_0
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 "google/gemma-4-12B-it-qat-q4_0-gguf:Q4_0" \ --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 google/gemma-4-12B-it-qat-q4_0-gguf with Docker Model Runner:
docker model run hf.co/google/gemma-4-12B-it-qat-q4_0-gguf:Q4_0
- Lemonade
How to use google/gemma-4-12B-it-qat-q4_0-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull google/gemma-4-12B-it-qat-q4_0-gguf:Q4_0
Run and chat with the model
lemonade run user.gemma-4-12B-it-qat-q4_0-gguf-Q4_0
List all available models
lemonade list
Tool Calls in LM Studio Not Working
When I try to connect an MCP server in LM Studio to this model I get the message shown below. Asking Gemini (Web) I believe it is a problem with the metadata setup for the model. I have also verified tool calls are working with other models on my machine in LM Studio (gemma-4-e4b)
"""
Failed to send message
Error rendering prompt with jinja template: "Cannot call something that is not a function: got UndefinedValue".
This is usually an issue with the model's prompt template. If you are using a popular model, you can try to search the model under lmstudio-community, which will have fixed prompt templates. If you cannot find one, you are welcome to post this issue to our discord or issue tracker on GitHub. Alternatively, if you know how to write jinja templates, you can override the prompt template in My Models > model settings > Prompt Template.
"""
is this working now?
I think it could have been an integration issue all Gemma models are pretty similar, so if it works with e4b, it should work with the 12B