Diffusers
Safetensors
WuerstchenPriorPipeline
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---
license: mit
---

## How to run

This pipeline should be run together with https://huggingface.co/warp-diffusion/wuerstchen:

```py
import torch                                                                                                                                                                                                                                                                    
from diffusers import WuerstchenDecoderPipeline, WuerstchenPriorPipeline                                                                                                                                                                                                        
                                                                                                                                                                                                                                                                                
device = "cuda"                                                                                                                                                                                                                                                                 
dtype = torch.float16                                                                                                                                                                                                                                                           
num_images_per_prompt = 2                                                                                                                                                                                                                                                       
                                                                                                                                                                                                                                                                                
prior_pipeline = WuerstchenPriorPipeline.from_pretrained(                                                                                                                                                                                                                       
    "warp-diffusion/wuerstchen-prior", torch_dtype=dtype                                                                                                                                                                                                                        
).to(device)                                                                                                                                                                                                                                                                    
decoder_pipeline = WuerstchenDecoderPipeline.from_pretrained(                                                                                                                                                                                                                   
    "warp-diffusion/wuerstchen", torch_dtype=dtype                                                                                                                                                                                                                              
).to(device)                                                                                                                                                                                                                                                                    
                                                                                                                                                                                                                                                                                
caption = "A captivating artwork of a mysterious stone golem"
negative_prompt = ""

prior_output = prior_pipeline(
    prompt=caption,
    height=1024,
    width=1024,
    negative_prompt=negative_prompt,
        guidance_scale=4.0,
    num_images_per_prompt=num_images_per_prompt,
)
decoder_output = decoder_pipeline(
    image_embeddings=prior_output.image_embeddings,
    prompt=caption,
    negative_prompt=negative_prompt,
    num_images_per_prompt=num_images_per_prompt,
    guidance_scale=0.0,
    output_type="pil",
).images
```