Instructions to use darkc0de/XORTRON-XPRT3-FAST 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 darkc0de/XORTRON-XPRT3-FAST 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 darkc0de/XORTRON-XPRT3-FAST:Q5_K_M # Run inference directly in the terminal: llama cli -hf darkc0de/XORTRON-XPRT3-FAST:Q5_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf darkc0de/XORTRON-XPRT3-FAST:Q5_K_M # Run inference directly in the terminal: llama cli -hf darkc0de/XORTRON-XPRT3-FAST:Q5_K_M
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 darkc0de/XORTRON-XPRT3-FAST:Q5_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf darkc0de/XORTRON-XPRT3-FAST:Q5_K_M
Use Docker
docker model run hf.co/darkc0de/XORTRON-XPRT3-FAST:Q5_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use darkc0de/XORTRON-XPRT3-FAST with Ollama:
ollama run hf.co/darkc0de/XORTRON-XPRT3-FAST:Q5_K_M
- Unsloth Desktop
- Pi
How to use darkc0de/XORTRON-XPRT3-FAST with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf darkc0de/XORTRON-XPRT3-FAST:Q5_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": "darkc0de/XORTRON-XPRT3-FAST:Q5_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use darkc0de/XORTRON-XPRT3-FAST with Docker Model Runner:
docker model run hf.co/darkc0de/XORTRON-XPRT3-FAST:Q5_K_M
- Lemonade
How to use darkc0de/XORTRON-XPRT3-FAST with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull darkc0de/XORTRON-XPRT3-FAST:Q5_K_M
Run and chat with the model
lemonade run user.XORTRON-XPRT3-FAST-Q5_K_M
List all available models
lemonade list
- Hermes Agent
How to use darkc0de/XORTRON-XPRT3-FAST with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf darkc0de/XORTRON-XPRT3-FAST:Q5_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 darkc0de/XORTRON-XPRT3-FAST:Q5_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use darkc0de/XORTRON-XPRT3-FAST with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf darkc0de/XORTRON-XPRT3-FAST:Q5_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 "darkc0de/XORTRON-XPRT3-FAST:Q5_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"
Amazing
This Model is very nice, Great Job!
Could you also please Upload the Full weights?
dude you've definitely got something dope going on, i like your little web os thing, looking forward to more dope resources from you brother
Extreamly fast,wow! Thank you!
Very impressive.
Just one thing, how to use the chat template with ollama ?
Do i need it ?
Бля, модель супер крутая! Почему так мало загрузок? Это ведь топ!!!!
Бля, модель супер крутая! Почему так мало загрузок? Это ведь топ!!!!
Вся серия xotron хороша. забавны были первые версии с большим пафосом рассуждающие. Правда лишние токены жрало. Загрузок мало потому, что подавляющее большинство и не знает о данном проекте.