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 / README.md

addy-hypr4

feat: restructure repo to match runtime, add missing piper voices, and update README/manifest

c9658c4 7 days ago

preview code

raw

history blame contribute delete

1.53 kB

	---
	license: apache-2.0
	tags:
	- voice
	- stt
	- tts
	- llm
	- vox
	- real-time
	- edge-inference
	library_name: generic
	---

	# 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:

	```text
	.
	├── 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](https://git-lfs.github.com/) installed to correctly retrieve the large model weights.