Instructions to use StationPC/Qwen3-8B-RKNN3-RK1828 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 StationPC/Qwen3-8B-RKNN3-RK1828 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 StationPC/Qwen3-8B-RKNN3-RK1828 # Run inference directly in the terminal: llama cli -hf StationPC/Qwen3-8B-RKNN3-RK1828
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf StationPC/Qwen3-8B-RKNN3-RK1828 # Run inference directly in the terminal: llama cli -hf StationPC/Qwen3-8B-RKNN3-RK1828
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 StationPC/Qwen3-8B-RKNN3-RK1828 # Run inference directly in the terminal: ./llama-cli -hf StationPC/Qwen3-8B-RKNN3-RK1828
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 StationPC/Qwen3-8B-RKNN3-RK1828 # Run inference directly in the terminal: ./build/bin/llama-cli -hf StationPC/Qwen3-8B-RKNN3-RK1828
Use Docker
docker model run hf.co/StationPC/Qwen3-8B-RKNN3-RK1828
- LM Studio
- Jan
- vLLM
How to use StationPC/Qwen3-8B-RKNN3-RK1828 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "StationPC/Qwen3-8B-RKNN3-RK1828" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "StationPC/Qwen3-8B-RKNN3-RK1828", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/StationPC/Qwen3-8B-RKNN3-RK1828
- Ollama
How to use StationPC/Qwen3-8B-RKNN3-RK1828 with Ollama:
ollama run hf.co/StationPC/Qwen3-8B-RKNN3-RK1828
- Unsloth Desktop
- Pi
How to use StationPC/Qwen3-8B-RKNN3-RK1828 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf StationPC/Qwen3-8B-RKNN3-RK1828
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": "StationPC/Qwen3-8B-RKNN3-RK1828" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use StationPC/Qwen3-8B-RKNN3-RK1828 with Docker Model Runner:
docker model run hf.co/StationPC/Qwen3-8B-RKNN3-RK1828
- Lemonade
How to use StationPC/Qwen3-8B-RKNN3-RK1828 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull StationPC/Qwen3-8B-RKNN3-RK1828
Run and chat with the model
lemonade run user.Qwen3-8B-RKNN3-RK1828-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use StationPC/Qwen3-8B-RKNN3-RK1828 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf StationPC/Qwen3-8B-RKNN3-RK1828
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 StationPC/Qwen3-8B-RKNN3-RK1828
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use StationPC/Qwen3-8B-RKNN3-RK1828 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf StationPC/Qwen3-8B-RKNN3-RK1828
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 "StationPC/Qwen3-8B-RKNN3-RK1828" \ --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 Qwen3-8B-6144.rknn with huggingface_hub
Browse files- .gitattributes +1 -0
- Qwen3-8B-6144.rknn +3 -0
.gitattributes
CHANGED
|
@@ -37,3 +37,4 @@ Qwen3-8B.rknn filter=lfs diff=lfs merge=lfs -text
|
|
| 37 |
Qwen3-8B.tokenizer.gguf filter=lfs diff=lfs merge=lfs -text
|
| 38 |
Qwen3-8B.weight filter=lfs diff=lfs merge=lfs -text
|
| 39 |
tokenizer.json filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 37 |
Qwen3-8B.tokenizer.gguf filter=lfs diff=lfs merge=lfs -text
|
| 38 |
Qwen3-8B.weight filter=lfs diff=lfs merge=lfs -text
|
| 39 |
tokenizer.json filter=lfs diff=lfs merge=lfs -text
|
| 40 |
+
Qwen3-8B-6144.rknn filter=lfs diff=lfs merge=lfs -text
|
Qwen3-8B-6144.rknn
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:40b2d02b070f5ab4a2a22e11a450a9cbfe64644b55d3d51c35faf6622f12ab45
|
| 3 |
+
size 44959640
|