 DreamBooth model for Starcraft:Remastered terrain  This is a Stable Diffusion model fine-tuned on Starcraft terrain images on the Space Platform tileset with DreamBooth. It can be used by adding the `instance_prompt`: **isometric scspace terrain**  It was trained on 32x32 terrain images from 265 melee maps including original Blizzard maps and those downloaded from Battle.net, scmscx.com and broodwarmaps.net.  Run it on Huggingface Spaces:  https://huggingface.co/spaces/wdcqc/wfd  Or use this notebook on Colab:  https://colab.research.google.com/github/wdcqc/WaveFunctionDiffusion/blob/remaster/colab/WaveFunctionDiffusion_Demo.ipynb  In addition to Dreambooth, a custom VAE model (`AutoencoderTile`) is trained to encode and decode the latents to/from tileset probabilities ("waves") and then generated as Starcraft maps.  A WFC Guidance, inspired by the Wave Function Collapse algorithm, is also added to the pipeline. For more information about guidance please see this page: [Fine-Tuning, Guidance and Conditioning](https://github.com/huggingface/diffusion-models-class/tree/main/unit2)  This model was created as part of the DreamBooth Hackathon. Visit the [organisation page](https://huggingface.co/dreambooth-hackathon) for instructions on how to take part!  