Instructions to use appvoid/void.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use appvoid/void.0 with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf appvoid/void.0
# Run inference directly in the terminal:
llama cli -hf appvoid/void.0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf appvoid/void.0
# Run inference directly in the terminal:
llama cli -hf appvoid/void.0

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 appvoid/void.0
# Run inference directly in the terminal:
./llama-cli -hf appvoid/void.0

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 appvoid/void.0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf appvoid/void.0

Use Docker

docker model run hf.co/appvoid/void.0

LM Studio
Jan
Ollama
How to use appvoid/void.0 with Ollama:
```
ollama run hf.co/appvoid/void.0
```

Unsloth Studio

How to use appvoid/void.0 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 appvoid/void.0 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 appvoid/void.0 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for appvoid/void.0 to start chatting

Docker Model Runner
How to use appvoid/void.0 with Docker Model Runner:
```
docker model run hf.co/appvoid/void.0
```

Lemonade

How to use appvoid/void.0 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull appvoid/void.0

Run and chat with the model

lemonade run user.void.0-{{QUANT_TAG}}

List all available models

lemonade list

Atomic Chat

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This repository is publicly accessible, but you have to accept the conditions to access its files and content.

Introducing void: our first ever language model, trained from scratch with a novel hybrid tokenizer on 300M high-quality tokens (total of 2 epochs on a B300) using 4096 as context window. Total cost was $23 dollars. It has around 140m parameters. Future releases are expected to be published in the following weeks.

Disclaimer: Even though the model is based on gemma 3 architecture, the tokenizer is different so you might need to wait until this model can be added to llama.cpp

If you want to sponsor future model releases, you can get information on how to make contributions here: CEAMFA

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