import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("eliftansusunar/xyz", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]xyz on Stable Diffusion via Dreambooth
model by eliftansusunar
This your the Stable Diffusion model fine-tuned the xyz concept taught to Stable Diffusion with Dreambooth.
You can also train your own concepts and upload them to the library by using this notebook.
And you can run your new concept via diffusers: Colab Notebook for Inference, Spaces with the Public Concepts loaded
Here are the images used for training this concept: .JPG) .jpg) .JPG) .jpg) .jpg) .JPG) .jpg) .JPG) .JPG) .jpg) .JPG) .jpg) .JPG) .jpg) .JPG) .jpg)
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