This repository contains Stable Diffusion’s implementation in PyTorch.
This isn't actually an implementation of stable diffusion from scratch. I cancelled this project and started working on RLHF
pip install -r requirements.txt
pip install -e .from PIL import Image
from foundation.stable_diffusion import StableDiffusion
prompt = "holy young female battle robot flying award winning, portrait bust symmetry faded tetrachromacycolors arctic background tim hildebrandt wayne barlowe bruce pennington donato giancola larry elmore masterpiece trending on artstation cinematic composition beautiful lighting hyper detailed!!! 8 k oil on canva"
model = StableDiffusion(n_inference_steps=30)
images = model.generate(prompt)
pil_images = [Image.fromarray(image) for image in images]
pil_images[0]
Variational Autoencoder (VAE) model with KL loss from the paper Auto-Encoding Variational Bayes by Diederik P. Kingma and Max Wellin
This repository is still a work in progress.
Currently, no downloads
and no executables are provided.
I welcome many contributors who can help.
Licensed under the MIT license.
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