Instructions to use Ruler97/Godoter-27B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Ruler97/Godoter-27B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Ruler97/Godoter-27B-GGUF",
	filename="Godoter-Q4_K_M.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Ruler97/Godoter-27B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Ruler97/Godoter-27B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Ruler97/Godoter-27B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Ruler97/Godoter-27B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Ruler97/Godoter-27B-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 Ruler97/Godoter-27B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Ruler97/Godoter-27B-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 Ruler97/Godoter-27B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Ruler97/Godoter-27B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/Ruler97/Godoter-27B-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use Ruler97/Godoter-27B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Ruler97/Godoter-27B-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": "Ruler97/Godoter-27B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Ruler97/Godoter-27B-GGUF:Q4_K_M

Ollama
How to use Ruler97/Godoter-27B-GGUF with Ollama:
```
ollama run hf.co/Ruler97/Godoter-27B-GGUF:Q4_K_M
```

Unsloth Studio

How to use Ruler97/Godoter-27B-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 Ruler97/Godoter-27B-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 Ruler97/Godoter-27B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Ruler97/Godoter-27B-GGUF to start chatting

How to use Ruler97/Godoter-27B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf Ruler97/Godoter-27B-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": "Ruler97/Godoter-27B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use Ruler97/Godoter-27B-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf Ruler97/Godoter-27B-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 Ruler97/Godoter-27B-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat new
Docker Model Runner
How to use Ruler97/Godoter-27B-GGUF with Docker Model Runner:
```
docker model run hf.co/Ruler97/Godoter-27B-GGUF:Q4_K_M
```

Lemonade

How to use Ruler97/Godoter-27B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Ruler97/Godoter-27B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Godoter-27B-GGUF-Q4_K_M

List all available models

lemonade list

Godoter — GGUF quantizations

Unofficial hobby project — NOT made by Godot. Godoter is a personal, non-commercial fine-tune made by an independent hobbyist for fun and learning. It is not made, created, maintained, affiliated with, sponsored by, or endorsed by the Godot Foundation or the Godot Engine team. "Godot" is a trademark of the Godot Foundation, used only to describe what the model is for. Base model: Qwen3.6-27B (Apache 2.0); training data includes the Godot documentation (CC-BY 4.0).

GGUF builds of Ruler97/Godoter-27B, a Qwen3.6-27B fine-tune specialized in Godot 4 / GDScript. Ready to drop into LM Studio, llama.cpp, Ollama or any GGUF runner.

Which file to download

File	Quant	Size	RAM/VRAM (rough)	When to use
`Godoter-Q4_K_M.gguf`	Q4_K_M	~16 GB	16 GB+	smallest & fastest, light quality loss
`Godoter-Q6_K.gguf`	Q6_K	~21 GB	24 GB+	recommended — best quality/size balance
`Godoter-Q8_0.gguf`	Q8_0	~27 GB	32 GB+	highest fidelity, closest to the merged model

If unsure, take Q6_K. Drop to Q4_K_M if you're tight on VRAM.

Benchmark (Q6, vs base Qwen3.6-27B)

Test	Base	Godoter
Easy tasks (Godot 4 migration traps)	80%	100%
Hard tasks (advanced Godot 4)	68%	96%

The base model, on hard questions, often drifts to the wrong framework (HTML/JS, Python, gRPC, Unity) or doesn't finish. Godoter stays anchored to Godot 4 GDScript and delivers correct, complete code.

How to run

LM Studio — put the file under models/<publisher>/Godoter/ and load it from the UI.

llama.cpp

llama-server -m Godoter-Q6_K.gguf -c 8192 --jinja -ngl 99
# then open http://127.0.0.1:8080

Ollama

# Modelfile
echo 'FROM ./Godoter-Q6_K.gguf' > Modelfile
ollama create godoter -f Modelfile
ollama run godoter "In Godot 4, connect a Button's pressed signal in code."

About the model

Fine-tune of unsloth/Qwen3.6-27B via QLoRA (r=16), trained on ~18,000 Godot 4 examples grounded in the official docs, plus 666 complete multi-file Godot 4 systems. See the main model card for full details.

License & attribution

Derivative of Qwen3.6-27B (Apache 2.0) — released under Apache 2.0. Built with Unsloth.

Downloads last month: 108

GGUF

Model size

27B params

Architecture

qwen35

Hardware compatibility

4-bit

6-bit

8-bit

Model tree for Ruler97/Godoter-27B-GGUF

Base model

Qwen/Qwen3.6-27B

Finetuned

unsloth/Qwen3.6-27B

Finetuned

Ruler97/Godoter-27B

Quantized

(3)

this model