Instructions to use OpenTARS/Gargantua-Pro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use OpenTARS/Gargantua-Pro 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 OpenTARS/Gargantua-Pro:Q4_K_M # Run inference directly in the terminal: llama cli -hf OpenTARS/Gargantua-Pro:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf OpenTARS/Gargantua-Pro:Q4_K_M # Run inference directly in the terminal: llama cli -hf OpenTARS/Gargantua-Pro:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf OpenTARS/Gargantua-Pro:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf OpenTARS/Gargantua-Pro:Q4_K_M
Use Docker
docker model run hf.co/OpenTARS/Gargantua-Pro:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use OpenTARS/Gargantua-Pro with Ollama:
ollama run hf.co/OpenTARS/Gargantua-Pro:Q4_K_M
- Unsloth Desktop
- Pi
How to use OpenTARS/Gargantua-Pro with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf OpenTARS/Gargantua-Pro:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "OpenTARS/Gargantua-Pro:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use OpenTARS/Gargantua-Pro with Docker Model Runner:
docker model run hf.co/OpenTARS/Gargantua-Pro:Q4_K_M
- Lemonade
How to use OpenTARS/Gargantua-Pro with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull OpenTARS/Gargantua-Pro:Q4_K_M
Run and chat with the model
lemonade run user.Gargantua-Pro-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use OpenTARS/Gargantua-Pro with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf OpenTARS/Gargantua-Pro: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 OpenTARS/Gargantua-Pro:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use OpenTARS/Gargantua-Pro with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf OpenTARS/Gargantua-Pro: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 "OpenTARS/Gargantua-Pro: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"
|
Download README.md from OpenTARS/Gargantua-Pro: direct link, hf CLI and curl.
- Browser
- Download file 1.31 kB
-
https://huggingface.co/OpenTARS/Gargantua-Pro/resolve/main/README.md
- Command line
-
hf download hf://OpenTARS/Gargantua-Pro/README.md
-
curl -L -o README.md https://huggingface.co/OpenTARS/Gargantua-Pro/resolve/main/README.md
1.31 kB
| license: apache-2.0 | |
| base_model: google/gemma-4-12b-it | |
| library_name: llama.cpp | |
| tags: | |
| - gguf | |
| - gemma4 | |
| - agent | |
| - tool-use | |
| - local | |
| language: | |
| - pt | |
| - en | |
| # Gargantua Pro (12B) | |
| Gargantua Pro is the big model of the [openTARS](https://project-opentars.github.io/OpenTARS/) assistant, built for longer tasks: plan the steps, call the tools, check the result and keep going until the job is done. It uses the same 19 tools as Gargantua 2, on a larger base. | |
| - **Base:** Gemma 4 12B (Apache-2.0), fine-tuned by the openTARS project on its own tool-use data. | |
| - **File:** `gargantua-pro-gemma4-12b-Q4_K_M.gguf` (7.4 GB, text only). | |
| - **Runs with:** llama.cpp and Ollama (the `gemma4` renderer and parser are built in). It needs a graphics card with about 8 GB, or plenty of RAM on the CPU. | |
| ## Use | |
| ```bash | |
| printf 'FROM ./gargantua-pro-gemma4-12b-Q4_K_M.gguf\nRENDERER gemma4\nPARSER gemma4\nPARAMETER temperature 0.1\n' > Modelfile | |
| ollama create gargantua-pro -f Modelfile | |
| ollama run gargantua-pro | |
| ``` | |
| It calls tools through the standard Ollama tool-calling API; the openTARS app sends the 19 tools for you. | |
| ## Status | |
| First release. We have not published benchmark numbers for it yet. | |
| Follow the project at [project-opentars.github.io/OpenTARS](https://project-opentars.github.io/OpenTARS/). | |