ComfyUI Node: DARE Merge LoRA Stack

DARE Merge LoRA Stack:

The DARE Merge LoRA Stack node is designed to facilitate the merging of multiple LoRA (Low-Rank Adaptation) models into a single set of weights, which can then be applied to a base model. This node is particularly useful for AI artists who want to combine the strengths of different LoRA models to enhance their generative models. By leveraging a dropout technique and spectral normalization, the node ensures that the merged weights are both robust and well-regularized. This process allows for more nuanced and controlled model adaptations, ultimately leading to higher-quality outputs in AI-generated art.

DARE Merge LoRA Stack Input Parameters:

lora_stack

This parameter accepts a stack of LoRA models that you wish to merge. Each item in the stack should be a tuple containing the LoRA model name, the strength for the model, and the strength for the clip. The stack allows you to combine multiple LoRA models, each contributing to the final merged weights.

lambda_val

This is a floating-point value that controls the scaling factor applied during the merging process. It influences the overall strength of the merged weights. The default value is 1.5, with a minimum of -4.0 and a maximum of 4.0. Adjusting this value can help fine-tune the balance between different LoRA models in the stack.

p

This parameter represents the dropout rate used in the merging process. It is a floating-point value between 0.01 and 1.0, with a default of 0.13. The dropout rate helps in regularizing the merged weights by randomly setting a fraction of the weights to zero, thus preventing overfitting.

scale

This floating-point value is used for spectral normalization of the merged weights. It helps in controlling the Lipschitz constant of the weights, ensuring that the merged model remains stable. The default value is 0.2, with a range from -1 to 10000.0. Adjusting this value can help in achieving the desired level of regularization.

seed

This integer value sets the random seed for the merging process, ensuring reproducibility of the results. The default value is 0, and it can range up to 0xffffffffffffffff. Setting a specific seed allows you to obtain consistent results across different runs.

DARE Merge LoRA Stack Output Parameters:

LoRA

The output of this node is a single set of merged LoRA weights. These weights can be applied to a base model to enhance its performance by incorporating the strengths of multiple LoRA models. The merged weights are regularized and scaled according to the input parameters, ensuring a balanced and robust adaptation.

DARE Merge LoRA Stack Usage Tips:

• Experiment with different values of lambda_val to find the optimal balance between the LoRA models in your stack.
• Use a higher p value if you notice overfitting in your merged model, as this will increase the dropout rate and improve regularization.
• Adjust the scale parameter to control the stability of the merged weights, especially if you are combining very different LoRA models.
• Set a specific seed value to ensure that you can reproduce your results in future runs.

DARE Merge LoRA Stack Common Errors and Solutions:

"Error loading LoRA model"

• Explanation: This error occurs when the specified LoRA model cannot be found or loaded.
• Solution: Ensure that the LoRA model names in the lora_stack parameter are correct and that the models are located in the appropriate directory.

"Invalid lambda_val"

• Explanation: This error occurs when the lambda_val parameter is set outside its allowed range.
• Solution: Adjust the lambda_val to be within the range of -4.0 to 4.0.

"Invalid p value"

• Explanation: This error occurs when the p parameter is set outside its allowed range.
• Solution: Adjust the p value to be within the range of 0.01 to 1.0.

"Invalid scale value"

• Explanation: This error occurs when the scale parameter is set outside its allowed range.
• Solution: Adjust the scale value to be within the range of -1 to 10000.0.

"Seed value out of range"

• Explanation: This error occurs when the seed parameter is set outside its allowed range.
• Solution: Adjust the seed value to be within the range of 0 to 0xffffffffffffffff.