Instructions to use Duino/my-uploaded-model 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 Duino/my-uploaded-model 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 Duino/my-uploaded-model # Run inference directly in the terminal: llama cli -hf Duino/my-uploaded-model
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Duino/my-uploaded-model # Run inference directly in the terminal: llama cli -hf Duino/my-uploaded-model
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 Duino/my-uploaded-model # Run inference directly in the terminal: ./build/bin/llama cli -hf Duino/my-uploaded-model
Use Docker
docker model run hf.co/Duino/my-uploaded-model
- Llama new
- LM Studio
- Jan
- Ollama
How to use Duino/my-uploaded-model with Ollama:
ollama run hf.co/Duino/my-uploaded-model
- Unsloth Desktop
- Pi
How to use Duino/my-uploaded-model with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Duino/my-uploaded-model
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": "Duino/my-uploaded-model" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use Duino/my-uploaded-model with Docker Model Runner:
docker model run hf.co/Duino/my-uploaded-model
- Lemonade
How to use Duino/my-uploaded-model with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Duino/my-uploaded-model
Run and chat with the model
lemonade run user.my-uploaded-model-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use Duino/my-uploaded-model with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Duino/my-uploaded-model
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 Duino/my-uploaded-model
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Duino/my-uploaded-model with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Duino/my-uploaded-model
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 "Duino/my-uploaded-model" \ --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"
Download Uncensor/duino.gguf from Duino/my-uploaded-model: direct link, hf CLI and curl.
- Browser
- Download file 13.1 GB
-
https://huggingface.co/Duino/my-uploaded-model/resolve/main/Uncensor/duino.gguf
- Command line
-
hf download hf://Duino/my-uploaded-model/Uncensor/duino.gguf
-
curl -L -o duino.gguf https://huggingface.co/Duino/my-uploaded-model/resolve/main/Uncensor/duino.gguf
13.1 GB
- Xet hash:
- 211f18169d9984f0037d3fa1afb5762850c77e12d8b9d9b4d666dc1ea52b31d0
- Size of remote file:
- 13.1 GB
- SHA256:
- 31472fdec8d431002c5be6fd35c4c3ec66ed9a97ee4d2e4459304067d723e8e7
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