Instructions to use addyo07/vox-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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.

Downloads last month: 36

GGUF

Model size

5B params

Architecture

gemma4

Hardware compatibility

2-bit

4-bit

6-bit

Inference Providers NEW

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