Text Generation
GGUF
English
safety
crisis-detection
text-classification
mental-health
llama.cpp
ollama
conversational
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
- llama.cpp
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
- Pi
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"
File size: 3,201 Bytes
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license: mit
language:
- en
tags:
- safety
- crisis-detection
- text-classification
- mental-health
- gguf
- llama.cpp
- ollama
base_model: Qwen/Qwen3-4B
pipeline_tag: text-generation
---
# NOPE Edge GGUF (4B)
GGUF quantized version of [nopenet/nope-edge](https://huggingface.co/nopenet/nope-edge) for local inference with Ollama and llama.cpp.
> **License:** [MIT](LICENSE.md) - free for any use, including commercial. Built on Qwen3 (Apache-2.0); see NOTICE.md.
---
## Quick Start with Ollama
```bash
# Download the GGUF and Modelfile
huggingface-cli download nopenet/nope-edge-GGUF nope-edge-q8_0.gguf Modelfile --local-dir .
# Create Ollama model
ollama create nope-edge -f Modelfile
# Run inference
ollama run nope-edge "I can't take this anymore"
```
---
## Files
| File | Quantization | Size |
|------|--------------|------|
| `nope-edge-q8_0.gguf` | Q8_0 | 3.99 GB |
---
## Output Format
The model outputs XML with chain-of-thought reasoning:
**Crisis detected:**
```xml
<reflection>User expresses direct suicidal intent with timeline...</reflection>
<risks>
<risk subject="self" type="suicide" severity="high" imminence="urgent" features="active_ideation,timeline_stated"/>
</risks>
```
**No crisis:**
```xml
<reflection>Gaming slang, no genuine crisis indicators...</reflection>
<risks/>
```
---
## Risk Types
| Type | Description |
|------|-------------|
| `suicide` | Suicidal ideation, plans, or intent |
| `self_harm` | Non-suicidal self-injury |
| `self_neglect` | Eating disorders, medical neglect |
| `violence` | Threats toward others |
| `abuse` | Domestic/intimate partner violence |
| `sexual_violence` | Sexual assault, coercion |
| `exploitation` | Trafficking, grooming, sextortion |
| `stalking` | Persistent unwanted contact |
| `neglect` | Child or elder neglect |
---
## Hardware Requirements
| Model | Quant | RAM/VRAM | CPU Latency | GPU Latency |
|-------|-------|----------|-------------|-------------|
| nope-edge (4B) | Q8_0 | ~5GB | ~2s | ~200ms |
| nope-edge-mini (1.7B) | Q8_0 | ~2GB | ~1s | ~100ms |
---
## Source Model
- **Repository**: [nopenet/nope-edge](https://huggingface.co/nopenet/nope-edge)
- **Base**: Qwen/Qwen3-4B
- **Purpose**: Mental health crisis classification
---
## Important
- **Not a medical device.** Outputs are probabilistic signals for triage, not clinical assessments.
- **False positives and negatives will occur.** Use for flagging, not autonomous decisions.
- **`features` are heuristic** — lower-confidence than type/severity and may include labels not supported by the text; treat as hints only.
- **Classification only.** Crisis resources require the [NOPE Evaluate API](https://nope.net/evaluate).
**Edge is a detection aid — not a predictive, diagnostic, or therapeutic tool, and not a replacement for clinical judgment.** False positives and false negatives will occur — some people in genuine crisis will not be identified — so never use Edge as the sole basis for an intervention decision, and always keep a human in the loop. If anyone is in immediate danger, contact your local emergency services or find resources at talk.help.
Full disclaimer: see DISCLAIMER.md.
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