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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.

Inputs

ParameterDescriptionData Type
modelSpecifies the model from which samples are to be generated, playing a crucial role in the sampling process.MODEL
add_noiseDetermines whether noise should be added to the sampling process, affecting the diversity and quality of the generated samples.COMBO[STRING]
noise_seedSets the seed for noise generation, ensuring reproducibility in the sampling process.INT
stepsDefines the number of steps to be taken in the sampling process, impacting the detail and quality of the output.INT
cfgControls the conditioning factor, influencing the direction and space of the sampling process.FLOAT
sampler_nameSelects the specific sampler to be used, allowing for customization of the sampling technique.COMBO[STRING]
schedulerChooses the scheduler for controlling the sampling process, affecting the progression and quality of samples.COMBO[STRING]
positiveSpecifies the positive conditioning to guide the sampling towards desired attributes.CONDITIONING
negativeSpecifies the negative conditioning to steer the sampling away from certain attributes.CONDITIONING
latent_imageProvides the initial latent image to be used in the sampling process, serving as a starting point.LATENT
start_at_stepDetermines the starting step of the sampling process, allowing for control over the sampling progression.INT
end_at_stepSets the ending step of the sampling process, defining the scope of the sampling.INT
return_with_leftover_noiseIndicates whether to return the sample with leftover noise, affecting the final output’s appearance.COMBO[STRING]

Outputs

ParameterDescriptionData Type
latentThe output represents the latent image generated from the model, reflecting the applied configurations and techniques.LATENT
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