Instructions to use Trilogix1/Hugston-Nex-N2-Pro-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Trilogix1/Hugston-Nex-N2-Pro-gguf with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Trilogix1/Hugston-Nex-N2-Pro-gguf", filename="Hugston-Nex-397B-A17B-BF16-mmproj.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Trilogix1/Hugston-Nex-N2-Pro-gguf with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Trilogix1/Hugston-Nex-N2-Pro-gguf:BF16 # Run inference directly in the terminal: llama-cli -hf Trilogix1/Hugston-Nex-N2-Pro-gguf:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Trilogix1/Hugston-Nex-N2-Pro-gguf:BF16 # Run inference directly in the terminal: llama-cli -hf Trilogix1/Hugston-Nex-N2-Pro-gguf:BF16
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 Trilogix1/Hugston-Nex-N2-Pro-gguf:BF16 # Run inference directly in the terminal: ./llama-cli -hf Trilogix1/Hugston-Nex-N2-Pro-gguf:BF16
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 Trilogix1/Hugston-Nex-N2-Pro-gguf:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Trilogix1/Hugston-Nex-N2-Pro-gguf:BF16
Use Docker
docker model run hf.co/Trilogix1/Hugston-Nex-N2-Pro-gguf:BF16
- LM Studio
- Jan
- Ollama
How to use Trilogix1/Hugston-Nex-N2-Pro-gguf with Ollama:
ollama run hf.co/Trilogix1/Hugston-Nex-N2-Pro-gguf:BF16
- Unsloth Studio
How to use Trilogix1/Hugston-Nex-N2-Pro-gguf with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Trilogix1/Hugston-Nex-N2-Pro-gguf to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Trilogix1/Hugston-Nex-N2-Pro-gguf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Trilogix1/Hugston-Nex-N2-Pro-gguf to start chatting
- Pi
How to use Trilogix1/Hugston-Nex-N2-Pro-gguf with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Trilogix1/Hugston-Nex-N2-Pro-gguf:BF16
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "Trilogix1/Hugston-Nex-N2-Pro-gguf:BF16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Trilogix1/Hugston-Nex-N2-Pro-gguf with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Trilogix1/Hugston-Nex-N2-Pro-gguf:BF16
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 Trilogix1/Hugston-Nex-N2-Pro-gguf:BF16
Run Hermes
hermes
- Atomic Chat new
- Docker Model Runner
How to use Trilogix1/Hugston-Nex-N2-Pro-gguf with Docker Model Runner:
docker model run hf.co/Trilogix1/Hugston-Nex-N2-Pro-gguf:BF16
- Lemonade
How to use Trilogix1/Hugston-Nex-N2-Pro-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Trilogix1/Hugston-Nex-N2-Pro-gguf:BF16
Run and chat with the model
lemonade run user.Hugston-Nex-N2-Pro-gguf-BF16
List all available models
lemonade list
- Credit to Qwen team for the model creation
- Credit to https://huggingface.co/nex-agi/Nex-N2-Pro for the finetunning method
- Credit to LLama.cpp team for the great contribution
- Credit to Hugston Team for Converting, Quantizing, Testing, Benching and other...
- Credit to Huggingface for the amazing hosting platform
This is a converted and quantized version of Qwen3.5 397B using Quanta and HugstonOne.
Author to finetuned model: https://huggingface.co/nex-agi/Nex-N2-Pro
The model is supposed to have been improved and optimized for agentic use beating GPT 5.5 and Opus 4.7 in at least one benchmark according to the authors. We would like to know more about the method and datasets used for the finetuning.
Credit to Qwen team for the model creation
Credit to https://huggingface.co/nex-agi/Nex-N2-Pro for the finetunning method
Credit to LLama.cpp team for the great contribution
Credit to Hugston Team for Converting, Quantizing, Testing, Benching and other...
Credit to Huggingface for the amazing hosting platform
Enjoy
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