import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("sd-dreambooth-library/brime", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]brime on Stable Diffusion via Dreambooth trained on the fast-DreamBooth.ipynb by TheLastBen notebook
model by samj
This your the Stable Diffusion model fine-tuned the brime concept taught to Stable Diffusion with Dreambooth.
It can be used by modifying the instance_prompt(s): prplbrime
You can also train your own concepts and upload them to the library by using the fast-DremaBooth.ipynb by TheLastBen.
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:
prplbrime
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