Instructions to use runanywhere/qwen3_8_27b_HNPU 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 runanywhere/qwen3_8_27b_HNPU 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 runanywhere/qwen3_8_27b_HNPU:UD-IQ1_M # Run inference directly in the terminal: llama cli -hf runanywhere/qwen3_8_27b_HNPU:UD-IQ1_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf runanywhere/qwen3_8_27b_HNPU:UD-IQ1_M # Run inference directly in the terminal: llama cli -hf runanywhere/qwen3_8_27b_HNPU:UD-IQ1_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 runanywhere/qwen3_8_27b_HNPU:UD-IQ1_M # Run inference directly in the terminal: ./llama-cli -hf runanywhere/qwen3_8_27b_HNPU:UD-IQ1_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 runanywhere/qwen3_8_27b_HNPU:UD-IQ1_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf runanywhere/qwen3_8_27b_HNPU:UD-IQ1_M
Use Docker
docker model run hf.co/runanywhere/qwen3_8_27b_HNPU:UD-IQ1_M
- LM Studio
- Jan
- vLLM
How to use runanywhere/qwen3_8_27b_HNPU with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "runanywhere/qwen3_8_27b_HNPU" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "runanywhere/qwen3_8_27b_HNPU", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/runanywhere/qwen3_8_27b_HNPU:UD-IQ1_M
- Ollama
How to use runanywhere/qwen3_8_27b_HNPU with Ollama:
ollama run hf.co/runanywhere/qwen3_8_27b_HNPU:UD-IQ1_M
- Unsloth Desktop
- Pi
How to use runanywhere/qwen3_8_27b_HNPU with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf runanywhere/qwen3_8_27b_HNPU:UD-IQ1_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": "runanywhere/qwen3_8_27b_HNPU:UD-IQ1_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use runanywhere/qwen3_8_27b_HNPU with Docker Model Runner:
docker model run hf.co/runanywhere/qwen3_8_27b_HNPU:UD-IQ1_M
- Lemonade
How to use runanywhere/qwen3_8_27b_HNPU with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull runanywhere/qwen3_8_27b_HNPU:UD-IQ1_M
Run and chat with the model
lemonade run user.qwen3_8_27b_HNPU-UD-IQ1_M
List all available models
lemonade list
- Hermes Agent
How to use runanywhere/qwen3_8_27b_HNPU with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf runanywhere/qwen3_8_27b_HNPU:UD-IQ1_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 runanywhere/qwen3_8_27b_HNPU:UD-IQ1_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use runanywhere/qwen3_8_27b_HNPU with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf runanywhere/qwen3_8_27b_HNPU:UD-IQ1_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 "runanywhere/qwen3_8_27b_HNPU:UD-IQ1_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"
Qwen3.8-27B — Hexagon NPU
Prebuilt Hexagon NPU artifacts for unsloth/Qwen3.8-27B-GGUF
(UD-IQ1_M), which is derived from Qwen/Qwen3.8-27B.
For model behaviour, intended use, limitations and licensing, see the upstream model cards linked above. Weights are redistributed unmodified under Apache 2.0, with attribution to their original authors.
Artifacts are arch-pinned; this repo currently contains a v81/ directory.
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