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
File size: 1,527 Bytes
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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
.
βββ manifest.json # Single source of truth for all models
βββ llm/
β βββ gemma4/ # Large Language Models (GGUF)
βββ stt/
β βββ qwen3-asr/ # Speech-to-Text (ONNX)
β βββ tokenizer/ # STT Tokenizer configs
βββ tts/
β βββ kokoro/ # English TTS (Kokoro ONNX)
β βββ piper_hi/ # Hindi TTS (Piper ONNX)
βββ vad/
βββ 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.
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