StableCascadeDecoderPipeline  
Pipeline for generating images from the Stable Cascade model.  
This model inherits from [`DiffusionPipeline`]. Check the superclass documentation for the generic methods the
library implements for all the pipelines (such as downloading or saving, running on a particular device, etc.)  
Args:
tokenizer (`CLIPTokenizer`):
The CLIP tokenizer.
text_encoder (`CLIPTextModel`):
The CLIP text encoder.
decoder ([`StableCascadeUNet`]):
The Stable Cascade decoder unet.
vqgan ([`PaellaVQModel`]):
The VQGAN model.
scheduler ([`DDPMWuerstchenScheduler`]):
A scheduler to be used in combination with `prior` to generate image embedding.
latent_dim_scale (float, `optional`, defaults to 10.67):
Multiplier to determine the VQ latent space size from the image embeddings. If the image embeddings are
height=24 and width=24, the VQ latent shape needs to be height=int(24*10.67)=256 and
width=int(24*10.67)=256 in order to match the training conditions.  
- all
- __call__
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/pipelines/stable_cascade.md