pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Cacau/anglarockone", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]anglarockone on Stable Diffusion via Dreambooth trained on the fast-DreamBooth.ipynb by TheLastBen notebook
Model by Cacau
This your the Stable Diffusion model fine-tuned the anglarockone concept taught to Stable Diffusion with Dreambooth.
It can be used by modifying the instance_prompt(s): anglarock(8).jpg, anglarock(14).jpg, anglarock(6).jpg, anglarock(2).jpg, anglarock(10).jpg
You can also train your own concepts and upload them to the library by using the fast-DremaBooth.ipynb by TheLastBen.
You can run your new concept via A1111 Colab :Fast-Colab-A1111
Or you can run your new concept via diffusers: Colab Notebook for Inference, Spaces with the Public Concepts loaded
Sample pictures of this concept:
anglarock(10).jpg
anglarock(2).jpg
anglarock(6).jpg
anglarock(14).jpg
anglarock(8).jpg
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