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stable-diffusion-v1-4 link in release v0.2.3 is broken

See original GitHub issue

Describe the bug

@anton-l the link (https://huggingface.co/CompVis/stable-diffusion-v1-4) in the release v0.2.3 returns a 404.

Reproduction

No response

Logs

No response

System Info

N/A

Issue Analytics

  • State:closed
  • Created a year ago
  • Comments:12 (5 by maintainers)

github_iconTop GitHub Comments

3reactions
anton-lcommented, Aug 22, 2022

@leszekhanusz we’re slightly ahead of schedule, the model repositories will be made public later today 😃

2reactions
leszekhanuszcommented, Aug 22, 2022

🔥 🔥 🚀 🚀 IT’S NOW AVAILABLE 🔥 🔥 🚀 🚀

Thank you!

Code used to test:

import torch                                                                                                            
import sys                                                                                                              
from torch import autocast                                                                                              
from diffusers import StableDiffusionPipeline, LMSDiscreteScheduler                                                     
                                                                                                                        
# this will substitute the default PNDM scheduler for K-LMS                                                             
lms = LMSDiscreteScheduler(                                                                                             
    beta_start=0.00085,                                                                                                 
    beta_end=0.012,                                                                                                     
    beta_schedule="scaled_linear"                                                                                       
)                                                                                                                       
                                                                                                                        
pipe = StableDiffusionPipeline.from_pretrained(                                                                         
    "CompVis/stable-diffusion-v1-4",                                                                                    
    revision="fp16",                                                                                                    
    torch_dtype=torch.float16,                                                                                          
    scheduler=lms,                                                                                                      
    use_auth_token=True                                                                                                 
).to("cuda")                                                                                                            
                                                                                                                        
while(True):                                                                                                            
    prompt = input("Prompt: ")                                                                                          
                                                                                                                        
    if len(prompt) == 0:                                                                                                
        break                                                                                                           
                                                                                                                        
    with autocast("cuda"):                                                                                              
        image = pipe(prompt)["sample"][0]                                                                               
                                                                                                                        
    image.show()                                                                                                        
    image.save(prompt + ".png")
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