ComfyUI Node: Primere Visual Hypernetwork Selector

Primere Visual Hypernetwork Selector:

PrimereVisualHypernetwork is a powerful node designed to enhance your AI-generated visuals by integrating hypernetworks into your model. This node allows you to apply multiple hypernetwork patches to your base model, enabling more complex and refined visual outputs. By leveraging hypernetworks, you can achieve a higher level of detail and stylistic variation in your generated images. The node is particularly useful for artists looking to push the boundaries of their AI models, offering a flexible and dynamic way to experiment with different visual styles and effects.

Primere Visual Hypernetwork Selector Input Parameters:

model

This parameter represents the base model to which the hypernetwork patches will be applied. It is essential for the node's operation as it serves as the foundation for all subsequent modifications.

model_version

This string parameter specifies the version of the model you are using. The default value is "BaseModel_1024". It is crucial for ensuring compatibility between the model and the hypernetwork patches.

safe_load

A boolean parameter that determines whether to safely load the hypernetwork patches. The default value is True. Enabling this option helps prevent potential issues during the loading process, ensuring a smoother and more reliable operation.

stack_version

This parameter allows you to specify the stack version, with options including "SD", "SDXL", and "Any". The default value is "Any". This setting helps tailor the hypernetwork application process to different model architectures.

use_hypernetwork_1

A boolean parameter that indicates whether to use the first hypernetwork. The default value is False. Enabling this option allows the first hypernetwork to be applied to the model.

hypernetwork_1

This parameter represents the first hypernetwork to be applied. It is selected from a list of available hypernetworks.

hypernetwork_1_weight

A float parameter that sets the weight of the first hypernetwork. The default value is 1.0, with a range from -10.0 to 10.0 and a step of 0.01. This weight determines the influence of the hypernetwork on the model.

use_hypernetwork_2

A boolean parameter that indicates whether to use the second hypernetwork. The default value is False. Enabling this option allows the second hypernetwork to be applied to the model.

hypernetwork_2

This parameter represents the second hypernetwork to be applied. It is selected from a list of available hypernetworks.

hypernetwork_2_weight

A float parameter that sets the weight of the second hypernetwork. The default value is 1.0, with a range from -10.0 to 10.0 and a step of 0.01. This weight determines the influence of the hypernetwork on the model.

use_hypernetwork_3

A boolean parameter that indicates whether to use the third hypernetwork. The default value is False. Enabling this option allows the third hypernetwork to be applied to the model.

hypernetwork_3

This parameter represents the third hypernetwork to be applied. It is selected from a list of available hypernetworks.

hypernetwork_3_weight

A float parameter that sets the weight of the third hypernetwork. The default value is 1.0, with a range from -10.0 to 10.0 and a step of 0.01. This weight determines the influence of the hypernetwork on the model.

use_hypernetwork_4

A boolean parameter that indicates whether to use the fourth hypernetwork. The default value is False. Enabling this option allows the fourth hypernetwork to be applied to the model.

hypernetwork_4

This parameter represents the fourth hypernetwork to be applied. It is selected from a list of available hypernetworks.

hypernetwork_4_weight

A float parameter that sets the weight of the fourth hypernetwork. The default value is 1.0, with a range from -10.0 to 10.0 and a step of 0.01. This weight determines the influence of the hypernetwork on the model.

use_hypernetwork_5

A boolean parameter that indicates whether to use the fifth hypernetwork. The default value is False. Enabling this option allows the fifth hypernetwork to be applied to the model.

hypernetwork_5

This parameter represents the fifth hypernetwork to be applied. It is selected from a list of available hypernetworks.

hypernetwork_5_weight

A float parameter that sets the weight of the fifth hypernetwork. The default value is 1.0, with a range from -10.0 to 10.0 and a step of 0.01. This weight determines the influence of the hypernetwork on the model.

use_hypernetwork_6

A boolean parameter that indicates whether to use the sixth hypernetwork. The default value is False. Enabling this option allows the sixth hypernetwork to be applied to the model.

hypernetwork_6

This parameter represents the sixth hypernetwork to be applied. It is selected from a list of available hypernetworks.

hypernetwork_6_weight

A float parameter that sets the weight of the sixth hypernetwork. The default value is 1.0, with a range from -10.0 to 10.0 and a step of 0.01. This weight determines the influence of the hypernetwork on the model.

Primere Visual Hypernetwork Selector Output Parameters:

MODEL

This output parameter represents the modified model after applying the selected hypernetwork patches. It serves as the enhanced version of your base model, incorporating the stylistic and detailed changes introduced by the hypernetworks.

HYPERNETWORK_STACK

This output parameter is a list that contains the stack of hypernetworks applied to the model, along with their respective weights. It provides a record of the hypernetworks used, allowing for reproducibility and further adjustments.

Primere Visual Hypernetwork Selector Usage Tips:

• Experiment with different hypernetwork weights to find the optimal balance for your desired visual effect.
• Use the safe_load option to prevent potential issues during the hypernetwork loading process.
• Combine multiple hypernetworks to achieve more complex and nuanced visual styles.

Primere Visual Hypernetwork Selector Common Errors and Solutions:

Hypernetwork patch loading failed

• Explanation: This error occurs when the node fails to load a hypernetwork patch.
• Solution: Ensure that the hypernetwork file exists and is accessible. Verify the file path and check for any file corruption.

Incompatible model version

• Explanation: This error occurs when the specified model version is not compatible with the hypernetwork patches.
• Solution: Verify that the model version matches the requirements of the hypernetwork patches. Adjust the model_version parameter accordingly.

Hypernetwork weight out of range

• Explanation: This error occurs when the hypernetwork weight is set outside the allowed range.
• Solution: Ensure that the hypernetwork weight is within the range of -10.0 to 10.0. Adjust the weight parameter to a valid value.