Instructions to use Jaj-Ajiq/KrunkQwen-4B-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 Jaj-Ajiq/KrunkQwen-4B-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 Jaj-Ajiq/KrunkQwen-4B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Jaj-Ajiq/KrunkQwen-4B-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 Jaj-Ajiq/KrunkQwen-4B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Jaj-Ajiq/KrunkQwen-4B-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 Jaj-Ajiq/KrunkQwen-4B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Jaj-Ajiq/KrunkQwen-4B-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 Jaj-Ajiq/KrunkQwen-4B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Jaj-Ajiq/KrunkQwen-4B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/Jaj-Ajiq/KrunkQwen-4B-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use Jaj-Ajiq/KrunkQwen-4B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Jaj-Ajiq/KrunkQwen-4B-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": "Jaj-Ajiq/KrunkQwen-4B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Jaj-Ajiq/KrunkQwen-4B-GGUF:Q4_K_M

Ollama
How to use Jaj-Ajiq/KrunkQwen-4B-GGUF with Ollama:
```
ollama run hf.co/Jaj-Ajiq/KrunkQwen-4B-GGUF:Q4_K_M
```
Unsloth Desktop

How to use Jaj-Ajiq/KrunkQwen-4B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Jaj-Ajiq/KrunkQwen-4B-GGUF: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": "Jaj-Ajiq/KrunkQwen-4B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Jaj-Ajiq/KrunkQwen-4B-GGUF with Docker Model Runner:
```
docker model run hf.co/Jaj-Ajiq/KrunkQwen-4B-GGUF:Q4_K_M
```

Lemonade

How to use Jaj-Ajiq/KrunkQwen-4B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Jaj-Ajiq/KrunkQwen-4B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.KrunkQwen-4B-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use Jaj-Ajiq/KrunkQwen-4B-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 Jaj-Ajiq/KrunkQwen-4B-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 Jaj-Ajiq/KrunkQwen-4B-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Jaj-Ajiq/KrunkQwen-4B-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Jaj-Ajiq/KrunkQwen-4B-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 "Jaj-Ajiq/KrunkQwen-4B-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"

KrunkQwen-4B

An experimental Qwen3 4B fine-tune for generating KrunkScript.

This is a fun side project, not a production-ready model. It can produce working KrunkScript for some basic requests, but quality is still poor. It may hallucinate APIs, mix in JavaScript syntax, or output broken code.

Simple LM Studio setup

Download and open LM studio.
Go to Model Search and download KrunkQwen-4B-Q4_K_M.gguf (search for KrunkQwen-4B-GGUF).
Load the model in Chat.
Set context length to 8192 or higher.
Open the system prompt from the GitHub repository: SYSTEM_PROMPT.md
Copy everything between BEGIN SYSTEM PROMPT and END SYSTEM PROMPT.
Paste it into LM Studio's System Prompt box.
Use:

Temperature: 0.1
Top P: 0.9
Max output tokens: 2000-4000

Test every generated script in the Krunker editor and report back if the script compiled or returned an error.

System prompt and project files

GitHub:

https://github.com/jajajiq/KrunkQwen-4B

Training summary

Base model: Qwen/Qwen3-4B-Instruct-2507
Method: Unsloth QLoRA
Epochs: 3
Training examples: 2,459
Quantization: Q4_K_M
DPO: not used

Limitations

KrunkQwen-4B may:

hallucinate nonexistent APIs;
output invalid KrunkScript;
mix in JavaScript syntax;
fail on complex or long requests;
produce incomplete or low-quality scripts.

The system prompt reduces mistakes but does not make the model reliable.

Future plans

A later version may use a much larger and cleaner public dataset, stronger and larger base models, better validation, more complete KrunkScript coverage, preference training, and stricter grammar checks.

Disclaimer

This is an independent community side project. It is not an official Krunker or KrunkScript project.

Downloads last month: 15

GGUF

Model size

4B params

Architecture

qwen3

Hardware compatibility

4-bit

Model tree for Jaj-Ajiq/KrunkQwen-4B-GGUF

Base model

Qwen/Qwen3-4B-Instruct-2507

Quantized

(323)

this model