Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input. For more information about how Stable Diffusion functions, please have a look at 🤗’s Stable Diffusion blog.
The Stable-Diffusion-v1-5 checkpoint was initialized with the weights of the Stable-Diffusion-v1-2 checkpoint and subsequently fine-tuned on 595k steps at resolution 512x512 on “laion-aesthetics v2 5+” and 10% dropping of the text-conditioning to improve classifier-free guidance sampling.
You can use this both with the 🧨Diffusers library and the RunwayML GitHub repository.
import cv2
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
pipe = pipeline(Tasks.text_to_image_synthesis, model='mushenL/breakdomain-anime', model_revision='v1.0.0')
output = pipe({'text': 'girl, Design a sorcerer who can communicate with animals, showcasing their magical talents and deep connection to the natural world.'})
cv2.imwrite('result.png', output['output_imgs'][0])
该模型可以像任何其他Stable Diffusion模型一样使用。
This model can be used just like any other Stable Diffusion model.