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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# NOPE Edge GGUF (4B)
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GGUF quantized
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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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## Files
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| `nope-edge-q8_0.gguf` | Q8_0 |
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---
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```xml
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<reflection>User expresses direct suicidal intent with timeline...</reflection>
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<risks>
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<risk subject="self" type="suicide" severity="high" imminence="urgent"
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</risks>
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```
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| Model | Quant | RAM/VRAM | CPU Latency | GPU Latency |
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| nope-edge (4B) | Q8_0 | ~5GB | ~2s | ~200ms |
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---
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- **Not a medical device.** Outputs are probabilistic signals for triage, not clinical assessments.
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- **False positives and negatives will occur.** Use for flagging, not autonomous decisions.
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# NOPE Edge GGUF (4B)
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GGUF quantized versions of [nopenet/nope-edge](https://huggingface.co/nopenet/nope-edge) for local inference with Ollama and llama.cpp.
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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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## Available Files
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| File | Quantization | Size | Use Case |
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| `nope-edge-q8_0.gguf` | Q8_0 | 4.0 GB | **Recommended** - best quality/size balance |
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| `nope-edge-q4_k_m.gguf` | Q4_K_M | 2.3 GB | Constrained environments |
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| `nope-edge-f16.gguf` | F16 | 7.5 GB | Maximum precision |
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---
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```xml
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<reflection>User expresses direct suicidal intent with timeline...</reflection>
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<risks>
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<risk subject="self" type="suicide" severity="high" imminence="urgent"/>
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</risks>
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```
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| Model | Quant | RAM/VRAM | CPU Latency | GPU Latency |
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| nope-edge (4B) | Q8_0 | ~5GB | ~2s | ~200ms |
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| nope-edge (4B) | Q4_K_M | ~3GB | ~1.5s | ~150ms |
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| nope-edge-mini (1.7B) | Q8_0 | ~2.5GB | ~1s | ~100ms |
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---
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## Model Variants
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| Model | Parameters | Use Case |
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| **[nope-edge](https://huggingface.co/nopenet/nope-edge)** | 4B | Maximum accuracy |
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| **[nope-edge-mini](https://huggingface.co/nopenet/nope-edge-mini)** | 1.7B | High-volume, cost-sensitive |
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GGUF versions:
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- **[nope-edge-GGUF](https://huggingface.co/nopenet/nope-edge-GGUF)** (this repo)
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- **[nope-edge-mini-GGUF](https://huggingface.co/nopenet/nope-edge-mini-GGUF)**
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---
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- **Not a medical device.** Outputs are probabilistic signals for triage, not clinical assessments.
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- **False positives and negatives will occur.** Use for flagging, not autonomous decisions.
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- **Human review required.** Never use as the sole basis for intervention decisions.
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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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