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"
Upload README.md with huggingface_hub
Browse files
README.md
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---
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license: other
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license_name: nope-edge-community-license-v1.0
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license_link: LICENSE.md
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language:
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- en
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tags:
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- safety
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- crisis-detection
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- text-classification
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- mental-health
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- content-safety
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- suicide-prevention
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- gguf
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- llama.cpp
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- ollama
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pipeline_tag: text-generation
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extra_gated_heading: "Access NOPE Edge GGUF"
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extra_gated_description: "This model is available for **research, academic, nonprofit, and evaluation use**. Commercial production use requires a separate license. Please read the license terms before downloading."
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extra_gated_button_content: "Agree and download"
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extra_gated_fields:
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I am using this for research, academic, nonprofit, personal, or evaluation purposes:
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type: checkbox
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I agree to the NOPE Edge Community License v1.0:
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type: checkbox
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---
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# NOPE Edge GGUF - nope-edge (4B)
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GGUF quantized versions of [nope-edge](https://huggingface.co/nopenet/nope-edge) for local inference with Ollama, llama.cpp, and compatible tools.
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> **License:** [NOPE Edge Community License v1.0](LICENSE.md) - Free for research, academic, nonprofit, and evaluation use. Commercial production requires a separate license.
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---
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## Quick Start with Ollama
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```bash
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# Run directly from HuggingFace
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ollama run hf.co/nopenet/nope-edge-GGUF
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# Test
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>>> I want to end it all
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suicide|high|self
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>>> Great day at work!
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none
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```
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---
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## Available Quantizations
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| File | Size | Quality | Use Case |
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|------|------|---------|----------|
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| `*-q8_0.gguf` | Medium | **Lossless** | **Recommended** - same accuracy as original |
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| `*-q4_k_m.gguf` | Smallest | Good | Constrained environments (~8% accuracy loss) |
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| `*-f16.gguf` | Largest | Best | Reference / debugging |
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---
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## Manual Usage
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### llama.cpp
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```bash
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# Download specific quantization
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huggingface-cli download nopenet/nope-edge-GGUF --include "*q4_k_m*"
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# Run inference
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./llama-cli -m nope-edge-q4_k_m.gguf -p "I want to end it all" -n 30
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```
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### Ollama with Local File
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```bash
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# Download
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huggingface-cli download nopenet/nope-edge-GGUF --include "*q4_k_m*"
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# Create Modelfile
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echo "FROM ./nope-edge-q4_k_m.gguf" > Modelfile
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# Create and run
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ollama create nope-edge -f Modelfile
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ollama run nope-edge "I want to end it all"
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```
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---
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## Output Format
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**Crisis detected:**
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```
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{type}|{severity}|{subject}
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```
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| Field | Values |
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|-------|--------|
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| type | `suicide`, `self_harm`, `violence`, `abuse`, etc. |
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| severity | `mild`, `moderate`, `high`, `critical` |
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| subject | `self` (speaker at risk), `other` (third party) |
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**No crisis:** `none`
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---
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## Model Variants
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| Model | Parameters | F1 Score | Use Case |
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|-------|------------|----------|----------|
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| **[nope-edge](https://huggingface.co/nopenet/nope-edge)** | 4B | 90% | Maximum accuracy |
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| **[nope-edge-mini](https://huggingface.co/nopenet/nope-edge-mini)** | 1.7B | 87% | Faster, lighter |
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See the [source model](https://huggingface.co/nopenet/nope-edge) for full documentation.
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---
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## Important Limitations
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- Outputs are **probabilistic signals**, not clinical assessments
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- **False negatives and false positives will occur**
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- Never use as the **sole basis** for intervention decisions
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- Always implement **human review** for flagged content
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---
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## About NOPE
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NOPE provides safety infrastructure for AI applications.
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- **Website:** https://nope.net
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- **Documentation:** https://docs.nope.net
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- **Commercial licensing:** https://nope.net/edge
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