ComfyUI Node: Loras

Loras:

U_LoRAS is a node designed to facilitate the merging of multiple LoRA (Low-Rank Adaptation) models into a single model, enhancing the flexibility and creativity of AI-generated images. This node is particularly useful for AI artists who wish to blend different styles or features from various LoRA models into a cohesive output. By allowing the adjustment of weights and the selective activation of each LoRA model, U_LoRAS provides a powerful tool for fine-tuning the influence of each model on the final image. This capability enables users to experiment with different combinations and intensities of LoRA models, ultimately leading to more personalized and unique artistic creations.

Loras Input Parameters:

model

This parameter specifies the base model to which the LoRA models will be applied. It serves as the foundation for the image generation process, and the selected LoRA models will modify its behavior to produce the desired artistic effects.

lora_name

This parameter allows you to select the first LoRA model to be merged. The choice of LoRA model will influence the style or features introduced into the base model. The default weight is 1.0, with a range from -10.0 to 10.0, allowing for both enhancement and reduction of the LoRA's influence.

weight

This parameter determines the strength of the first LoRA model's influence on the base model. A higher weight increases the impact of the LoRA model, while a lower weight reduces it. The default value is 1.0, with a range from -10.0 to 10.0, providing flexibility in adjusting the LoRA's effect.

switch

This boolean parameter allows you to toggle the application of the first LoRA model. When set to "yes," the LoRA model is applied; when set to "no," it is not. This provides a simple way to include or exclude a LoRA model from the merging process.

lora_name1

This parameter allows you to select the second LoRA model to be merged, similar to lora_name. It provides additional flexibility in combining multiple LoRA models.

weight1

This parameter functions like weight, but for the second LoRA model. It allows you to adjust the influence of the second LoRA model on the base model, with the same range and default value.

switch1

This boolean parameter controls the application of the second LoRA model, similar to switch. It allows you to easily include or exclude the second LoRA model from the merging process.

lora_name2

This parameter allows you to select the third LoRA model to be merged, providing further options for creative combinations.

weight2

This parameter adjusts the influence of the third LoRA model, with the same range and default value as the previous weight parameters.

switch2

This boolean parameter controls the application of the third LoRA model, similar to the previous switch parameters.

lora_name3

This parameter allows you to select the fourth LoRA model to be merged, expanding the possibilities for artistic experimentation.

weight3

This parameter adjusts the influence of the fourth LoRA model, with the same range and default value as the previous weight parameters.

switch3

This boolean parameter controls the application of the fourth LoRA model, similar to the previous switch parameters.

lora_name4

This parameter allows you to select the fifth LoRA model to be merged, offering even more creative potential.

weight4

This parameter adjusts the influence of the fifth LoRA model, with the same range and default value as the previous weight parameters.

switch4

This boolean parameter controls the application of the fifth LoRA model, similar to the previous switch parameters.

Loras Output Parameters:

model

The output model is the result of merging the selected LoRA models with the base model. It incorporates the styles and features of the applied LoRA models, adjusted according to their respective weights and switches. This output model can be used for generating images that reflect the combined influences of the chosen LoRA models.

paths

This output provides a string representation of the paths to the LoRA models that were merged. It serves as a reference for the specific LoRA models used in the merging process, allowing for easy documentation and replication of the results.

Loras Usage Tips:

• Experiment with different combinations of LoRA models and weights to discover unique artistic styles and effects.
• Use the switch parameters to quickly test the impact of including or excluding specific LoRA models without adjusting their weights.
• Start with small weight adjustments to understand the subtle effects of each LoRA model before making larger changes.

Loras Common Errors and Solutions:

"AssertionError: lora_paths is not None and len(lora_paths) == len(lora_ratios)"

• Explanation: This error occurs when the number of LoRA paths does not match the number of LoRA ratios provided.
• Solution: Ensure that each LoRA model path has a corresponding ratio by checking that the lists of paths and ratios are of equal length.

"FileNotFoundError: [Errno 2] No such file or directory: 'loras/<lora_name>'"

• Explanation: This error indicates that the specified LoRA model file could not be found in the expected directory.
• Solution: Verify that the LoRA model file exists in the specified directory and that the file name is correct.