> [!TIP]
> Refer to the scheduler API [overview](../api/schedulers/overview) for a list of schedulers that support Karras sigmas.
>
> Karras sigmas should not be used for models that weren't trained with them. For example, the base Stable Diffusion XL model shouldn't use Karras sigmas but the [DreamShaperXL](https://hf.co/Lykon/dreamshaper-xl-1-0) model can since they are trained with Karras sigmas.  
Karras scheduler's use the timestep schedule and sigmas from the [Elucidating the Design Space of Diffusion-Based Generative Models](https://hf.co/papers/2206.00364) paper. This scheduler variant applies a smaller amount of noise per step as it approaches the end of the sampling process compared to other schedulers, and can increase the level of details in the generated image.  
Enable Karras sigmas by setting `use_karras_sigmas=True` in the scheduler.  
```py
import torch
from diffusers import StableDiffusionXLPipeline, DPMSolverMultistepScheduler

pipeline = StableDiffusionXLPipeline.from_pretrained(
"SG161222/RealVisXL_V4.0",
torch_dtype=torch.float16,
variant="fp16",
).to("cuda")
pipeline.scheduler = DPMSolverMultistepScheduler.from_config(pipeline.scheduler.config, algorithm_type="sde-dpmsolver++", use_karras_sigmas=True)

prompt = "A cinematic shot of a cute little rabbit wearing a jacket and doing a thumbs up"
generator = torch.Generator(device="cpu").manual_seed(2487854446)
image = pipeline(
prompt=prompt,
negative_prompt="",
generator=generator,
).images[0]
```  
<div class="flex gap-4">
<div>
<img class="rounded-xl" src="https://huggingface.co/datasets/stevhliu/testing-images/resolve/main/karras_sigmas_true.png"/>
<figcaption class="mt-2 text-center text-sm text-gray-500">Karras sigmas enabled</figcaption>
</div>
<div>
<img class="rounded-xl" src="https://huggingface.co/datasets/stevhliu/testing-images/resolve/main/karras_sigmas_false.png"/>
<figcaption class="mt-2 text-center text-sm text-gray-500">Karras sigmas disabled</figcaption>
</div>
</div>
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/using-diffusers/scheduler_features.md