The `height` and `width` parameters control the height and width (in pixels) of the generated image. By default, the Stable Diffusion v1.5 model outputs 512x512 images, but you can change this to any size that is a multiple of 8. For example, to create a rectangular image:  
```py
from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained(
"stable-diffusion-v1-5/stable-diffusion-v1-5", torch_dtype=torch.float16, variant="fp16"
).to("cuda")
image = pipeline(
"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k", height=768, width=512
).images[0]
image
```  
<div class="flex justify-center">
<img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/text2img-hw.png"/>
</div>  
<Tip warning={true}>  
Other models may have different default image sizes depending on the image sizes in the training dataset. For example, SDXL's default image size is 1024x1024 and using lower `height` and `width` values may result in lower quality images. Make sure you check the model's API reference first!  
</Tip>
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/using-diffusers/conditional_image_generation.md