readme: ---
  license: openrail
  ---
  pip install --upgrade diffusers transformers scipy
  huggingface-cli login
  import torch
  from torch import autocast
  from diffusers import StableDiffusionPipeline
  
  model_id = "CompVis/stable-diffusion-v1-4"
  device = "cuda"
  
  
  pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=True)
  pipe = pipe.to(device)
  
  prompt = "a photo of an astronaut riding a horse on mars"
  with autocast("cuda"):
      image = pipe(prompt, guidance_scale=7.5).images[0]  
      
  image.save("astronaut_rides_horse.png")
  import torch
  
  pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16, revision="fp16", use_auth_token=True)
  pipe = pipe.to(device)
  
  prompt = "a photo of an astronaut riding a horse on mars"
  with autocast("cuda"):
      image = pipe(prompt, guidance_scale=7.5).images[0]  
      
  image.save("astronaut_rides_horse.png")
  from diffusers import StableDiffusionPipeline, LMSDiscreteScheduler
  
  model_id = "CompVis/stable-diffusion-v1-4"
  # Use the K-LMS scheduler here instead
  scheduler = LMSDiscreteScheduler(beta_start=0.00085, beta_end=0.012, beta_schedule="scaled_linear", num_train_timesteps=1000)
  pipe = StableDiffusionPipeline.from_pretrained(model_id, scheduler=scheduler, use_auth_token=True)
  pipe = pipe.to("cuda")
  
  prompt = "a photo of an astronaut riding a horse on mars"
  with autocast("cuda"):
      image = pipe(prompt, guidance_scale=7.5).images[0]  
      
  image.save("astronaut_rides_horse.png")
  