KSampler (Advanced)

Documentation

Class name: KSamplerAdvanced
Category: sampling
Output node: False

The KSamplerAdvanced node is designed to enhance the sampling process by providing advanced configurations and techniques. It aims to offer more sophisticated options for generating samples from a model, improving upon the basic KSampler functionalities.

Input types

Parameter	Comfy dtype	Description
`model`	MODEL	Specifies the model from which samples are to be generated, playing a crucial role in the sampling process.
`add_noise`	COMBO[STRING]	Determines whether noise should be added to the sampling process, affecting the diversity and quality of the generated samples.
`noise_seed`	INT	Sets the seed for noise generation, ensuring reproducibility in the sampling process.
`steps`	INT	Defines the number of steps to be taken in the sampling process, impacting the detail and quality of the output.
`cfg`	FLOAT	Controls the conditioning factor, influencing the direction and space of the sampling process.
`sampler_name`	COMBO[STRING]	Selects the specific sampler to be used, allowing for customization of the sampling technique.
`scheduler`	COMBO[STRING]	Chooses the scheduler for controlling the sampling process, affecting the progression and quality of samples.
`positive`	CONDITIONING	Specifies the positive conditioning to guide the sampling towards desired attributes.
`negative`	CONDITIONING	Specifies the negative conditioning to steer the sampling away from certain attributes.
`latent_image`	LATENT	Provides the initial latent image to be used in the sampling process, serving as a starting point.
`start_at_step`	INT	Determines the starting step of the sampling process, allowing for control over the sampling progression.
`end_at_step`	INT	Sets the ending step of the sampling process, defining the scope of the sampling.
`return_with_leftover_noise`	COMBO[STRING]	Indicates whether to return the sample with leftover noise, affecting the final output’s appearance.

Output types

Parameter	Comfy dtype	Description
`latent`	LATENT	The output represents the latent image generated from the model, reflecting the applied configurations and techniques.