Games
Collection
Diffusion models that I trained to render a game with user input as conditioning. • 4 items • Updated • 1
The unconditional Breakout world model used as the starting point for the playable version.
128x128 at 6 FPS with 12 frames of latent history. The model has about 70M parameters and uses the frozen SDXL VAE from madebyollin/sdxl-vae-fp16-fix.
Requires a CUDA GPU with BF16 support.
pip install torch numpy pillow safetensors huggingface_hub diffusers
hf download kerzgrr/diffusionbreakout-base live_infer.py --local-dir .
python live_infer.py --steps 1
To download everything first:
hf download kerzgrr/diffusionbreakout-base \
--local-dir checkpoints/diffusionbreakout-base \
--include "ema.safetensors" \
--include "config.json" \
--include "live_infer.py"
python checkpoints/diffusionbreakout-base/live_infer.py \
--local-dir checkpoints/diffusionbreakout-base \
--steps 1 \
--window-scale 6
This model is unconditional, so there are no paddle controls. It rolls forward from a fresh game context.
| file | contents |
|---|---|
ema.safetensors |
unconditional EMA weights |
config.json |
model, video, codec, and training settings |
live_infer.py |
single-file live inference |
preview.png |
validation strip |