ComfyUI Node: 💊 CR Random Weight LoRA

💊 CR Random Weight LoRA:

The CR Random Weight LoRA node is designed to add a LoRA (Low-Rank Adaptation) instance to a stack with a randomized weight within a specified range. This node is particularly useful for AI artists who want to introduce variability and randomness into their models, ensuring that the LoRA weights are not static and can change dynamically based on the defined parameters. The primary goal of this node is to enhance the creative process by allowing for more diverse and unpredictable outcomes, which can be particularly beneficial in generative art and other creative AI applications. By setting a stride, you can control the number of iterations before the weight is re-randomized, adding another layer of control and customization to your workflow.

💊 CR Random Weight LoRA Input Parameters:

stride

The stride parameter sets the number of iterations before the weight is re-randomized. This allows you to control how frequently the weight changes, providing a balance between stability and variability. The default value is 1, with a minimum of 1 and a maximum of 1000.

force_randomize_after_stride

The force_randomize_after_stride parameter determines whether the weight should be forcibly re-randomized after the specified stride. This can be set to "On" or "Off", with "Off" being the default. When set to "On", it ensures that the weight is always re-randomized after the stride, adding an extra layer of randomness.

lora_name

The lora_name parameter specifies the name of the LoRA instance to be added to the stack. If set to "None", no LoRA instance will be added. This parameter is crucial for identifying which LoRA instance you want to work with.

switch

The switch parameter controls whether the LoRA instance is active or not. It can be set to "On" or "Off", with "Off" being the default. When set to "On", the specified LoRA instance is added to the stack with the randomized weight.

weight_min

The weight_min parameter sets the minimum value for the randomized weight. This allows you to define the lower bound of the weight range, ensuring that the weight does not go below a certain value. The default value is 0.0.

weight_max

The weight_max parameter sets the maximum value for the randomized weight. This allows you to define the upper bound of the weight range, ensuring that the weight does not exceed a certain value. The default value is 1.0.

clip_weight

The clip_weight parameter specifies the weight to be applied to the CLIP model. This allows you to control the influence of the LoRA instance on the CLIP model, providing another layer of customization. The default value is 1.0.

lora_stack

The lora_stack parameter is an optional list of existing LoRA instances. If provided, the new LoRA instance with the randomized weight will be added to this stack. This allows for the creation of complex LoRA chains, enhancing the flexibility and creativity of your models.

💊 CR Random Weight LoRA Output Parameters:

lora_list

The lora_list output parameter is a list of tuples, each containing the name of the LoRA instance, its randomized weight, and the clip weight. This list represents the stack of LoRA instances that have been processed by the node, providing a comprehensive overview of the applied LoRA instances and their respective weights.

💊 CR Random Weight LoRA Usage Tips:

• To achieve more dynamic and varied results, set the force_randomize_after_stride parameter to "On" and experiment with different stride values.
• Use the weight_min and weight_max parameters to fine-tune the range of the randomized weights, ensuring that the weights stay within a desired range.
• Combine multiple LoRA instances by providing a lora_stack to create complex and interesting effects in your models.

💊 CR Random Weight LoRA Common Errors and Solutions:

"Invalid stride value"

• Explanation: The stride value provided is outside the allowed range (1-1000).
• Solution: Ensure that the stride value is within the range of 1 to 1000.

"LoRA name is None"

• Explanation: The lora_name parameter is set to "None", so no LoRA instance is added to the stack.
• Solution: Provide a valid LoRA name to add an instance to the stack.

"Switch is Off"

• Explanation: The switch parameter is set to "Off", so the LoRA instance is not active.
• Solution: Set the switch parameter to "On" to activate the LoRA instance.

"Weight range is invalid"

• Explanation: The weight_min value is greater than the weight_max value.
• Solution: Ensure that the weight_min value is less than or equal to the weight_max value.