---
title: GameScaling action viewer
emoji: 🎮
colorFrom: red
colorTo: green
sdk: static
app_file: index.html
short_description: A GameScaling reply as a mouse move and six 33 ms steps
license: apache-2.0
models:
- THUSI-Lab/GameScaling
---

# GameScaling — one 200 ms action chunk, visualised

A small static page for [GameScaling](https://huggingface.co/THUSI-Lab/GameScaling)
(*Scaling in Games: Continued Pre-Training for Embodied Agents in Diverse Virtual Worlds*).

Every turn the model answers with exactly one chunk:

```
<|action_start|>X Y Z ; g1 ; g2 ; g3 ; g4 ; g5 ; g6<|action_end|>
```

`X Y` is the mouse displacement over the whole 200 ms in per-mille of the screen, `Z` the scroll
amount, and `g1..g6` are the keys held during each of six 33 ms sub-steps.

This page parses such a reply and draws it: the red arrow is the predicted mouse move, the strip below
tells you what is held when. Press **Play** to step through the chunk.

**There is no model here.** The Doom reply is a recorded output shipped by the authors
(`examples/doom_battle1_action.txt`); paste any other reply into the box to parse it.
Live inference lives in the authors' [ZeroGPU Space](https://huggingface.co/spaces/THUSI-Lab/gamescaling) —
Gradio/Docker Spaces need a PRO plan, and the 2B/9B checkpoints need a GPU, so this copy is the static,
free-hardware option.

The parser and overlay geometry follow the authors' `gamescaling` package (Apache-2.0), reimplemented in
plain JavaScript. Not affiliated with the authors.

Frame credits:
- `doom_battle1.jpg`: from the authors' repo.
- `minetest.jpg`: "Minetest screenshot 2" by Kotolegokot, CC BY-SA 3.0, via Wikimedia Commons.
- `supertuxkart.jpg`: "Supertuxkart-0.9-screenshot-2" by the SuperTuxKart dev team, CC BY 3.0, via Wikimedia Commons.