import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("arnaudstiegler/gameNgen-baseline-20ksteps", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]GameNgen fine-tuning - arnaudstiegler/gameNgen-baseline-20ksteps
Full finetune of CompVis/stable-diffusion-v1-4. The weights were fine-tuned on the P-H-B-D-a16z/ViZDoom-Deathmatch-PPO-Lrg dataset. You can find some example images in the following.
Intended uses & limitations
How to use
See: https://github.com/arnaudstiegler/gameNgen-repro/blob/main/README.md
Training details
20k steps batch size 12 10 epochs with CFG data augmentation
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Model tree for arnaudstiegler/gameNgen-baseline-20ksteps
Base model
CompVis/stable-diffusion-v1-4