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Converts text numerical values to sigmas for AI computations, simplifying tensor creation for machine learning.
The Sigmas From Text
node is designed to convert a string of numerical values into a tensor of sigmas, which are used in various computational processes, particularly in AI and machine learning tasks. This node is particularly useful for transforming human-readable text input into a format that can be processed by machine learning models. By allowing you to input a series of numbers as text, it simplifies the process of creating a tensor, which is a multi-dimensional array used extensively in AI computations. This node is essential for users who need to input custom sigma values directly from text, making it easier to experiment with different configurations and observe their effects on model performance.
The text
parameter is a string input that allows you to provide a series of numerical values separated by spaces or commas. These values are converted into a tensor of sigmas, which are used in various AI computations. The input should be a valid string of numbers, and it supports multiline input, making it flexible for longer lists of values. There are no explicit minimum or maximum values for this parameter, but the numbers should be formatted correctly to ensure successful conversion.
The sigmas
output is a tensor containing the numerical values provided in the text
input, converted into a format suitable for computational tasks. This tensor is crucial for processes that require sigma values, such as noise scheduling in diffusion models. The output tensor is created on the GPU (CUDA) and is of type torch.float64
, ensuring high precision for subsequent calculations.
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