Ten demos of d1-3B. Each one asks the model a few typed questions about a camera frame,
a drawing or a message, and reads the answers from one forward pass.
| demo | what it shows |
|---|---|
| Hand Flappy | open your palm to fly up, close it to drop |
| Pong vs the Model | the model plays from a text description of the game |
| Rep Counter | counts squats, jumping jacks or arm raises |
| Keep It Clean | pixelates the middle finger, 0.4 s behind the camera |
| Find It | show the camera each object it asks for |
| Quick Draw | it guesses your drawing among 16 words |
| Red Light, Green Light | move on green, freeze on red |
| Cowboy Duel | two players, first finger gun wins |
| Live Triage | six answers about a support message as you type |
| Ask Anything | your own yes/no questions about the camera image |
Camera frames go to the model on this Space's GPU and are not stored.
Here every frame makes a round trip to the Space's server, about 0.2 s, which the games that react to each frame (Flappy, Pong, Duel, Red Light) can feel. On your own machine a decision comes back in tens of milliseconds.
You need an Apple silicon Mac, or Linux (WSL2 works) with an NVIDIA GPU of 8 GB or more, and Python 3.12 or newer.
git clone https://huggingface.co/spaces/LiquidAI/system-one-arcade
cd system-one-arcade
python3 -m venv .venv && source .venv/bin/activate
On an Apple silicon Mac (PyTorch on mps):
pip install -r requirements-mac.txt
python game/server.py
On an NVIDIA GPU (PyTorch, CUDA graphs):
pip install -r requirements-nvidia.txt
python game/server.py --compile
Open the address it prints; it carries a token, so other machines on your network cannot use the
server. The first start downloads the model (6.2 GB) and warms up for a minute or two; if the
download asks for a login, run hf auth login first.
python game/server.py --help lists the options (port, model, frame size).
Settings:
HF_TOKEN, a token that can read the model.Ten demos of d1-3B. Each one asks the model a few typed questions about a camera frame,
a drawing or a message, and reads the answers from one forward pass.
| demo | what it shows |
|---|---|
| Hand Flappy | open your palm to fly up, close it to drop |
| Pong vs the Model | the model plays from a text description of the game |
| Rep Counter | counts squats, jumping jacks or arm raises |
| Keep It Clean | pixelates the middle finger, 0.4 s behind the camera |
| Find It | show the camera each object it asks for |
| Quick Draw | it guesses your drawing among 16 words |
| Red Light, Green Light | move on green, freeze on red |
| Cowboy Duel | two players, first finger gun wins |
| Live Triage | six answers about a support message as you type |
| Ask Anything | your own yes/no questions about the camera image |
Camera frames go to the model on this Space's GPU and are not stored.
Here every frame makes a round trip to the Space's server, about 0.2 s, which the games that react to each frame (Flappy, Pong, Duel, Red Light) can feel. On your own machine a decision comes back in tens of milliseconds.
You need an Apple silicon Mac, or Linux (WSL2 works) with an NVIDIA GPU of 8 GB or more, and Python 3.12 or newer.
git clone https://huggingface.co/spaces/LiquidAI/system-one-arcade
cd system-one-arcade
python3 -m venv .venv && source .venv/bin/activate
On an Apple silicon Mac (PyTorch on mps):
pip install -r requirements-mac.txt
python game/server.py
On an NVIDIA GPU (PyTorch, CUDA graphs):
pip install -r requirements-nvidia.txt
python game/server.py --compile
Open the address it prints; it carries a token, so other machines on your network cannot use the
server. The first start downloads the model (6.2 GB) and warms up for a minute or two; if the
download asks for a login, run hf auth login first.
python game/server.py --help lists the options (port, model, frame size).
Settings:
HF_TOKEN, a token that can read the model.