



import torch

from diffusers import StableDiffusionPipeline


lowercase_						=       """path-to-your-trained-model"""
lowercase_						=       StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("""cuda""")

lowercase_						=       """A photo of sks dog in a bucket"""
lowercase_						=       pipe(prompt, num_inference_steps=50, guidance_scale=7.5).images[0]

image.save("""dog-bucket.png""")









from collections import namedtuple

import requests
from lxml import html  # type: ignore

lowercase_						=       namedtuple("""covid_data""", """cases deaths recovered""")



def __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_ = "https://www.worldometers.info/coronavirus/"					):
			lowercase__   					=			"//div[@class = \"maincounter-number\"]/span/text()"
			return covid_data(*html.fromstring(requests.get(SCREAMING_SNAKE_CASE_					).content					).xpath(SCREAMING_SNAKE_CASE_					)					)


lowercase_						=       """Total COVID-19 cases in the world: {}
Total deaths due to COVID-19 in the world: {}
Total COVID-19 patients recovered in the world: {}"""




print(fmt.format(*covid_stats()))




