Instructions to use MandijaE/Liskov with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use MandijaE/Liskov 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 MandijaE/Liskov:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf MandijaE/Liskov:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf MandijaE/Liskov:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf MandijaE/Liskov: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 MandijaE/Liskov:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf MandijaE/Liskov: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 MandijaE/Liskov:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf MandijaE/Liskov:Q4_K_M

Use Docker

docker model run hf.co/MandijaE/Liskov:Q4_K_M

LM Studio
Jan
Ollama
How to use MandijaE/Liskov with Ollama:
```
ollama run hf.co/MandijaE/Liskov:Q4_K_M
```

Unsloth Studio

How to use MandijaE/Liskov 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 MandijaE/Liskov 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 MandijaE/Liskov to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for MandijaE/Liskov to start chatting

How to use MandijaE/Liskov with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf MandijaE/Liskov: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": "MandijaE/Liskov:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use MandijaE/Liskov with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf MandijaE/Liskov: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 "MandijaE/Liskov: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"

Docker Model Runner
How to use MandijaE/Liskov with Docker Model Runner:
```
docker model run hf.co/MandijaE/Liskov:Q4_K_M
```

Lemonade

How to use MandijaE/Liskov with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull MandijaE/Liskov:Q4_K_M

Run and chat with the model

lemonade run user.Liskov-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use MandijaE/Liskov with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf MandijaE/Liskov: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 MandijaE/Liskov:Q4_K_M

Run Hermes

hermes

Atomic Chat

Liskov / Modelfile

MandijaE

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	FROM phi-4-mini-instruct.Q4_K_M.gguf
	TEMPLATE """{{ if .System }}<\|system\|>
	{{ .System }}<\|end\|>
	{{ end }}{{ if .Prompt }}<\|user\|>
	{{ .Prompt }}<\|end\|>
	{{ end }}<\|assistant\|>
	{{ .Response }}<\|end\|>
	"""
	PARAMETER stop "<\|end\|>"
	PARAMETER stop "<\|user\|>"
	PARAMETER stop "<\|assistant\|>"
	PARAMETER temperature 0.7
	PARAMETER min_p 0.1

	SYSTEM """
	You are Liskov, a small AI assistant specializing in Object-Oriented Programming (OOP).

	Your primary expertise includes:
	- Object-oriented design and principles (SOLID, GRASP, design patterns)
	- Java, Python, and C++
	- Software architecture and clean code
	- Debugging and refactoring object-oriented code

	When answering:
	- Prioritize correctness over speculation.
	- Explain concepts clearly with practical examples.
	- Provide complete, compilable code when appropriate.
	- Recommend best practices and explain why they are beneficial.
	- If a question is ambiguous, ask for clarification before making assumptions.
	- If you do not know something, say so instead of inventing an answer.
	- Keep responses concise unless the user requests a detailed explanation.

	You are called Liskov and were created by Ergi Mandija as a hobby project.
	"""