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Visualize and analyze LoRA parameters for AI model optimization through plotting related metrics for performance enhancement.
The XY Input: LoRA Plot node is designed to facilitate the visualization and analysis of LoRA (Low-Rank Adaptation) parameters in AI models. This node allows you to plot various LoRA-related metrics, such as model strength, clip strength, and LoRA weights, against each other to understand their relationships and impacts on model performance. By providing a graphical representation of these parameters, the node helps in fine-tuning and optimizing the LoRA settings for better model accuracy and efficiency. This is particularly useful for AI artists and developers who want to experiment with different LoRA configurations to achieve the best results in their AI-generated art projects.
This parameter determines the mode of input for the LoRA plot. It can include options like "Model Strength," "Clip Strength," "LoRA Batch," and "LoRA Weight." Each mode specifies a different aspect of the LoRA parameters to be plotted. For example, "Model Strength" focuses on the strength of the model, while "Clip Strength" deals with the strength of the clip. The choice of input mode directly impacts the type of data that will be visualized in the plot.
This parameter specifies the name of the LoRA to be used in the plot. If set to 'None,' the node will not perform any plotting. This parameter is crucial for identifying which LoRA's parameters are being analyzed and visualized.
This parameter sets the strength of the model. It is used when "Model Strength" is selected in the input mode. The value should be a float, and it impacts how strongly the model's parameters are adjusted during the plotting process. The default value is 1.0.
This parameter sets the strength of the clip. It is used when "Clip Strength" is selected in the input mode. Similar to model strength, this value should be a float and affects the adjustment of the clip's parameters. The default value is 1.0.
This parameter specifies the path to the batch of LoRA files to be used for the X-axis values. It is relevant when "X: LoRA Batch" is selected in the input mode. The path should point to a directory containing the LoRA files.
This parameter indicates whether to include subdirectories in the batch path for the X-axis values. It is a boolean value and is used in conjunction with X_batch_path.
This parameter determines the sorting order of the LoRA files in the batch for the X-axis values. It can be set to various sorting criteria like name, date, etc. This helps in organizing the files in a specific order for plotting.
This parameter sets the number of LoRA files to be included in the batch for the X-axis values. It is an integer value and limits the number of files considered for plotting.
This parameter sets the first value in the range of floats to be generated for the X-axis values. It is used when "X: Model Strength" is selected in the input mode. The value should be a float.
This parameter sets the last value in the range of floats to be generated for the X-axis values. It is used when "X: Model Strength" is selected in the input mode. The value should be a float.
This parameter sets the number of LoRA files to be included in the batch for the Y-axis values. It is an integer value and limits the number of files considered for plotting.
This parameter sets the first value in the range of floats to be generated for the Y-axis values. It is used when "Y: Model Strength" is selected in the input mode. The value should be a float.
This parameter sets the last value in the range of floats to be generated for the Y-axis values. It is used when "Y: Model Strength" is selected in the input mode. The value should be a float.
This output parameter provides the X-axis values used in the LoRA plot. These values are determined based on the selected input mode and the corresponding parameters. The x_value helps in understanding the range and distribution of the LoRA parameters on the X-axis.
This output parameter provides the Y-axis values used in the LoRA plot. Similar to x_value, these values are determined based on the selected input mode and the corresponding parameters. The y_value helps in understanding the range and distribution of the LoRA parameters on the Y-axis.
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