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Versatile node for precise sigma value control in AI art sampling, enabling customized noise schedules for higher-quality outputs.
The Manual scheduler is a versatile node designed to provide you with precise control over the scheduling of sigma values during the sampling process. This node is particularly useful for AI artists who want to fine-tune the noise levels at each step of their model's sampling process, allowing for more customized and potentially higher-quality outputs. By manually specifying the sigma values, you can experiment with different noise schedules to achieve the desired artistic effect, making this node an essential tool for those looking to push the boundaries of their creative projects.
This parameter specifies the model to be used for sampling. It is a required input and ensures that the scheduler has the necessary model context to generate sigma values.
This integer parameter determines the number of steps in the sampling process. The default value is 10, with a minimum of 1 and a maximum of 10000. Adjusting this parameter affects the granularity of the sampling process, with more steps providing finer control over the noise levels.
This parameter allows you to select the type of model you are using, with options including "SD1", "SDXL", and "SVD". This selection helps the scheduler to align its sigma values with the specific characteristics of the chosen model type.
This boolean parameter, which defaults to False, determines whether the minimum sigma value should be forced. When set to True, the scheduler ensures that the minimum sigma value is included in the generated sigma values, which can be useful for certain types of sampling processes.
The output of the Manual scheduler is a tensor of sigma values. These values represent the noise levels at each step of the sampling process, allowing you to control the denoising process precisely. The sigma values are crucial for achieving the desired artistic effect, as they influence the level of detail and smoothness in the generated images.
steps
values to find the optimal balance between detail and smoothness in your images.model_type
parameter to ensure that the sigma values are aligned with the specific characteristics of your model, which can improve the quality of the output.force_sigma_min
parameter to True to ensure it is part of the generated sigma values.model
parameter is not provided.model
parameter before running the scheduler.steps
parameter is set to a value outside the allowed range (1 to 10000).steps
parameter to a value within the allowed range.model_type
parameter.force_sigma_min
parameter is not set to a boolean value.force_sigma_min
parameter is set to either True or False.© Copyright 2024 RunComfy. All Rights Reserved.