Instructions to use zero2root/mythos-coder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use zero2root/mythos-coder 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 zero2root/mythos-coder:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf zero2root/mythos-coder:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf zero2root/mythos-coder:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf zero2root/mythos-coder: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 zero2root/mythos-coder:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf zero2root/mythos-coder: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 zero2root/mythos-coder:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf zero2root/mythos-coder:Q4_K_M

Use Docker

docker model run hf.co/zero2root/mythos-coder:Q4_K_M

LM Studio
Jan
Ollama
How to use zero2root/mythos-coder with Ollama:
```
ollama run hf.co/zero2root/mythos-coder:Q4_K_M
```

Unsloth Studio

How to use zero2root/mythos-coder 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 zero2root/mythos-coder 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 zero2root/mythos-coder to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for zero2root/mythos-coder to start chatting

How to use zero2root/mythos-coder with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf zero2root/mythos-coder: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": "zero2root/mythos-coder:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use zero2root/mythos-coder with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf zero2root/mythos-coder: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 "zero2root/mythos-coder: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 zero2root/mythos-coder with Docker Model Runner:
```
docker model run hf.co/zero2root/mythos-coder:Q4_K_M
```

Lemonade

How to use zero2root/mythos-coder with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull zero2root/mythos-coder:Q4_K_M

Run and chat with the model

lemonade run user.mythos-coder-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use zero2root/mythos-coder with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf zero2root/mythos-coder: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 zero2root/mythos-coder:Q4_K_M

Run Hermes

hermes

Atomic Chat

mythos-coder — Q4_K_M (GGUF)

Fine-tuned Qwen2.5-Coder-1.5B that writes Python exploit-detection code for the MYTHOS autonomous offensive security platform.

Base model: Qwen/Qwen2.5-Coder-1.5B
Quantization: Q4_K_M
Size: 941 MB (986,048,064 bytes)
Context: 32,768
SHA-256: 58e8bbd6c22aac2fbb0daf921b1329d75d72a4a397197b01f19f039363b656a5

System prompt

You are MYTHOS, an autonomous offensive security AI that writes Python code to
detect and exploit vulnerabilities. You output ONLY valid Python code.
No explanations, no thinking tags.

Usage with Ollama

ollama create mythos-coder -f Modelfile
# Modelfile:
#   FROM mythos-coder-Q4_K_M.gguf
#   PARAMETER temperature 0.1
#   PARAMETER top_p 0.95
#   PARAMETER num_ctx 2048

Usage in MYTHOS

The MYTHOS project (scripts/provision_models.sh) consumes this file automatically via the URL below — set MYTHOS_GGUF_URL and the model builds itself during setup:

MYTHOS_GGUF_URL=https://huggingface.co/zero2root/mythos-coder/resolve/main/mythos-coder-Q4_K_M.gguf

Ethical use

For authorized penetration testing and defensive research only. Use only against systems you own or are explicitly permitted to test.

Downloads last month: 137

GGUF

Model size

2B params

Architecture

qwen2

Hardware compatibility

4-bit

Inference Providers NEW

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Model tree for zero2root/mythos-coder

Base model

Qwen/Qwen2.5-1.5B

Finetuned

Qwen/Qwen2.5-Coder-1.5B

Quantized

(50)

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