How to use from the
Use from the
Diffusers library
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("sd-dreambooth-library/musecat-ppt-model", dtype=torch.bfloat16, device_map="cuda")

prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]

musecat_PPt_Model on Stable Diffusion via Dreambooth

model by LK0608

This your the Stable Diffusion model fine-tuned the musecat_PPt_Model concept taught to Stable Diffusion with Dreambooth. It can be used by modifying the instance_prompt: a photo of a mscds cat

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: image 0 image 1 image 2 image 3

Here are the images generated by the original model:

image 0 image 1 image 2 image 3 image 4 image 5 image 6 image 7 image 8 image 9 image 10 image 11

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