Instructions to use nopenet/nope-edge-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 nopenet/nope-edge-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 nopenet/nope-edge-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf nopenet/nope-edge-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 nopenet/nope-edge-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf nopenet/nope-edge-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 nopenet/nope-edge-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf nopenet/nope-edge-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 nopenet/nope-edge-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf nopenet/nope-edge-GGUF:Q4_K_M

Use Docker

docker model run hf.co/nopenet/nope-edge-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use nopenet/nope-edge-GGUF with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/nopenet/nope-edge-GGUF:Q4_K_M

Ollama
How to use nopenet/nope-edge-GGUF with Ollama:
```
ollama run hf.co/nopenet/nope-edge-GGUF:Q4_K_M
```
Unsloth Desktop

How to use nopenet/nope-edge-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf nopenet/nope-edge-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": "nopenet/nope-edge-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use nopenet/nope-edge-GGUF with Docker Model Runner:
```
docker model run hf.co/nopenet/nope-edge-GGUF:Q4_K_M
```

Lemonade

How to use nopenet/nope-edge-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull nopenet/nope-edge-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.nope-edge-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use nopenet/nope-edge-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 nopenet/nope-edge-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 nopenet/nope-edge-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use nopenet/nope-edge-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf nopenet/nope-edge-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 "nopenet/nope-edge-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"

nope-edge-GGUF / LICENSE.md

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	# MIT License

	Copyright (c) 2026 NopeNet, LLC

	Permission is hereby granted, free of charge, to any person obtaining a copy
	of this software and associated documentation and model files (the "Software"),
	to deal in the Software without restriction, including without limitation the
	rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
	copies of the Software, and to permit persons to whom the Software is furnished
	to do so, subject to the following conditions:

	The above copyright notice and this permission notice shall be included in all
	copies or substantial portions of the Software.

	THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
	IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
	FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
	COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
	IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
	CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

	---

	The MIT grant above is the complete licence for NOPE Edge — free for any use,
	including commercial, with no separate agreement required ("Software" = the model
	weights and accompanying files). Before deploying a life-safety classifier,
	please read DISCLAIMER.md (intended use, non-claims, and important
	limitations) and NOTICE.md (attribution for the Qwen3 base model, which is
	licensed under Apache-2.0).