import torch
from diffusers import DiffusionPipeline
from diffusers.utils import load_image
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Sanster/PowerPaint-V1-stable-diffusion-inpainting", dtype=torch.bfloat16, device_map="cuda")
prompt = "Turn this cat into a dog"
input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
image = pipe(image=input_image, prompt=prompt).images[0]YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Model from: https://huggingface.co/JunhaoZhuang/PowerPaint-v1
Based on runwayml/stable-diffusion-inpainting, the unet has been replaced with PowerPaint's unet,
and the token embedding (P_ctxt, P_shape, P_obj) newly added by PowerPaint has been integrated into the text_encoder.
Download python file at here, then run:
python3 demo.py
- Downloads last month
- 1,438