Instructions to use bytkim/Qwen3.6-27B-MTP-pi-tune-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 bytkim/Qwen3.6-27B-MTP-pi-tune-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 bytkim/Qwen3.6-27B-MTP-pi-tune-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf bytkim/Qwen3.6-27B-MTP-pi-tune-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 bytkim/Qwen3.6-27B-MTP-pi-tune-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf bytkim/Qwen3.6-27B-MTP-pi-tune-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 bytkim/Qwen3.6-27B-MTP-pi-tune-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf bytkim/Qwen3.6-27B-MTP-pi-tune-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 bytkim/Qwen3.6-27B-MTP-pi-tune-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf bytkim/Qwen3.6-27B-MTP-pi-tune-GGUF:Q4_K_M

Use Docker

docker model run hf.co/bytkim/Qwen3.6-27B-MTP-pi-tune-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use bytkim/Qwen3.6-27B-MTP-pi-tune-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "bytkim/Qwen3.6-27B-MTP-pi-tune-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": "bytkim/Qwen3.6-27B-MTP-pi-tune-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/bytkim/Qwen3.6-27B-MTP-pi-tune-GGUF:Q4_K_M

Ollama
How to use bytkim/Qwen3.6-27B-MTP-pi-tune-GGUF with Ollama:
```
ollama run hf.co/bytkim/Qwen3.6-27B-MTP-pi-tune-GGUF:Q4_K_M
```
Unsloth Desktop

How to use bytkim/Qwen3.6-27B-MTP-pi-tune-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf bytkim/Qwen3.6-27B-MTP-pi-tune-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": "bytkim/Qwen3.6-27B-MTP-pi-tune-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use bytkim/Qwen3.6-27B-MTP-pi-tune-GGUF with Docker Model Runner:
```
docker model run hf.co/bytkim/Qwen3.6-27B-MTP-pi-tune-GGUF:Q4_K_M
```

Lemonade

How to use bytkim/Qwen3.6-27B-MTP-pi-tune-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull bytkim/Qwen3.6-27B-MTP-pi-tune-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Qwen3.6-27B-MTP-pi-tune-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use bytkim/Qwen3.6-27B-MTP-pi-tune-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 bytkim/Qwen3.6-27B-MTP-pi-tune-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 bytkim/Qwen3.6-27B-MTP-pi-tune-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use bytkim/Qwen3.6-27B-MTP-pi-tune-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf bytkim/Qwen3.6-27B-MTP-pi-tune-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 "bytkim/Qwen3.6-27B-MTP-pi-tune-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"

is supports opencode?

by dfsafdsf - opened Jun 21

Discussion

dfsafdsf

Jun 21

•

edited Jun 21

hello, i use ohmyopenagent with opencode. Your model is better Qwen3.6 in this concrete case (my current model - qwopus 3.6 27b) ?

bytkim

Owner Jun 27

Hey dfsafdsf,

It is difficult to say without knowing your setup and launch config.

I would recommend independently testing the two models and evaluating on real world tasks that you might encounter.

This way you are able to make the judgement accurately yourself.

Any discoveries or additional information that might be helpful are always appreciated.

Thank you!

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