KarrasVeScheduler  
A stochastic scheduler tailored to variance-expanding models.  
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic
methods the library implements for all schedulers such as loading and saving.  
<Tip>  
For more details on the parameters, see [Appendix E](https://arxiv.org/abs/2206.00364). The grid search values used
to find the optimal `{s_noise, s_churn, s_min, s_max}` for a specific model are described in Table 5 of the paper.  
</Tip>  
Args:
sigma_min (`float`, defaults to 0.02):
The minimum noise magnitude.
sigma_max (`float`, defaults to 100):
The maximum noise magnitude.
s_noise (`float`, defaults to 1.007):
The amount of additional noise to counteract loss of detail during sampling. A reasonable range is [1.000,
1.011].
s_churn (`float`, defaults to 80):
The parameter controlling the overall amount of stochasticity. A reasonable range is [0, 100].
s_min (`float`, defaults to 0.05):
The start value of the sigma range to add noise (enable stochasticity). A reasonable range is [0, 10].
s_max (`float`, defaults to 50):
The end value of the sigma range to add noise. A reasonable range is [0.2, 80].
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/schedulers/stochastic_karras_ve.md