Instructions to use addyo07/vox-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use addyo07/vox-models with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="addyo07/vox-models", filename="llm/gemma4/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive-Q2_K_P.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use addyo07/vox-models with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf addyo07/vox-models:Q4_K_M # Run inference directly in the terminal: llama-cli -hf addyo07/vox-models:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf addyo07/vox-models:Q4_K_M # Run inference directly in the terminal: llama-cli -hf addyo07/vox-models:Q4_K_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 addyo07/vox-models:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf addyo07/vox-models:Q4_K_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 addyo07/vox-models:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf addyo07/vox-models:Q4_K_M
Use Docker
docker model run hf.co/addyo07/vox-models:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use addyo07/vox-models with Ollama:
ollama run hf.co/addyo07/vox-models:Q4_K_M
- Unsloth Studio new
How to use addyo07/vox-models 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 addyo07/vox-models 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 addyo07/vox-models to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for addyo07/vox-models to start chatting
- Pi new
How to use addyo07/vox-models with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf addyo07/vox-models:Q4_K_M
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": "addyo07/vox-models:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use addyo07/vox-models with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf addyo07/vox-models:Q4_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 addyo07/vox-models:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use addyo07/vox-models with Docker Model Runner:
docker model run hf.co/addyo07/vox-models:Q4_K_M
- Lemonade
How to use addyo07/vox-models with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull addyo07/vox-models:Q4_K_M
Run and chat with the model
lemonade run user.vox-models-Q4_K_M
List all available models
lemonade list
Vox Models
This repository serves as the official model host for Vox, a real-time, local-first voice-to-voice system. It contains specialized models for Voice Activity Detection (VAD), Speech-to-Text (STT), Large Language Models (LLM), and Text-to-Speech (TTS).
Directory Structure
The structure of this repository exactly mirrors the runtime expectations of the Vox backend:
.
├── manifest.json # Single source of truth for all models
├── llm/
│ └── gemma4/ # Large Language Models (GGUF)
├── stt/
│ └── qwen3-asr/ # Speech-to-Text (ONNX)
│ └── tokenizer/ # STT Tokenizer configs
├── tts/
│ ├── kokoro/ # English TTS (Kokoro ONNX)
│ └── piper_hi/ # Hindi TTS (Piper ONNX)
└── vad/
└── ten_vad.onnx # Voice Activity Detection (ONNX)
Manifest
The manifest.json file in the root directory provides metadata for automated management, including:
- Relative file paths
- Exact byte sizes
- SHA256 hashes for integrity verification
- Archive markers for compressed assets (e.g.,
espeak-ng-data)
Usage
These models are intended to be downloaded and managed by the Vox application runtime. For manual use, ensure you have Git LFS installed to correctly retrieve the large model weights.
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