Instructions to use orcarouter/OrcaCyber-Nano-1.0 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 orcarouter/OrcaCyber-Nano-1.0 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 orcarouter/OrcaCyber-Nano-1.0:Q8_0 # Run inference directly in the terminal: llama cli -hf orcarouter/OrcaCyber-Nano-1.0:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf orcarouter/OrcaCyber-Nano-1.0:Q8_0 # Run inference directly in the terminal: llama cli -hf orcarouter/OrcaCyber-Nano-1.0:Q8_0
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf orcarouter/OrcaCyber-Nano-1.0:Q8_0 # Run inference directly in the terminal: ./build/bin/llama cli -hf orcarouter/OrcaCyber-Nano-1.0:Q8_0
Use Docker
docker model run hf.co/orcarouter/OrcaCyber-Nano-1.0:Q8_0
- Llama new
- LM Studio
- Jan
- vLLM
How to use orcarouter/OrcaCyber-Nano-1.0 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "orcarouter/OrcaCyber-Nano-1.0" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "orcarouter/OrcaCyber-Nano-1.0", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/orcarouter/OrcaCyber-Nano-1.0:Q8_0
- Ollama
How to use orcarouter/OrcaCyber-Nano-1.0 with Ollama:
ollama run hf.co/orcarouter/OrcaCyber-Nano-1.0:Q8_0
- Unsloth Desktop
- Pi
How to use orcarouter/OrcaCyber-Nano-1.0 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf orcarouter/OrcaCyber-Nano-1.0:Q8_0
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": "orcarouter/OrcaCyber-Nano-1.0:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use orcarouter/OrcaCyber-Nano-1.0 with Docker Model Runner:
docker model run hf.co/orcarouter/OrcaCyber-Nano-1.0:Q8_0
- Lemonade
How to use orcarouter/OrcaCyber-Nano-1.0 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull orcarouter/OrcaCyber-Nano-1.0:Q8_0
Run and chat with the model
lemonade run user.OrcaCyber-Nano-1.0-Q8_0
List all available models
lemonade list
- Hermes Agent
How to use orcarouter/OrcaCyber-Nano-1.0 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf orcarouter/OrcaCyber-Nano-1.0:Q8_0
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 orcarouter/OrcaCyber-Nano-1.0:Q8_0
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use orcarouter/OrcaCyber-Nano-1.0 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf orcarouter/OrcaCyber-Nano-1.0:Q8_0
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 "orcarouter/OrcaCyber-Nano-1.0:Q8_0" \ --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"
Redistribution terms for the Mix-13G target, vision projector and DFlash2 draft
Hello OrcaRouter team,
We have published a runtime-only package for the original OrcaCyber Nano 1.0 GGUFs, with attribution, pinned source hashes, portable llama.cpp helpers, and measured Apple Silicon results:
https://huggingface.co/3hs4n/OrcaCyber-Nano-1.0-GGUF-Mix-13G-Optimized-DFlash2
It currently downloads all model files from your gated original repository; it contains no weights. However, GGUF model pickers cannot use a runtime-only repository for one-click downloads.
Could you point us to the complete applicable model license and confirm whether we may mirror these three files unchanged, with the original terms, hashes, attribution and source links preserved?
- OrcaCyber-Nano-1.0-AI-Defense-Mix-13G.gguf
- mmproj-OrcaCyber-Nano-1.0-AI-Defense-F16.gguf
- OrcaCyber-Nano-1.0-AI-Defense-DFlash2-Q8_0.gguf
The source revision is 1af1635aa22b97e965450c2d69525761d9bd463f. We found the metadata license: other / license_name: qwen, but no complete license file. Please also clarify whether the drafter has separate terms and whether an authorized mirror must preserve a gate.
No model weights have been changed or redistributed in our package.