ComfyUI Node: Automatic CFG - Negative

Automatic CFG - Negative:

The Automatic CFG

• Negative node is designed to enhance the performance of AI models by dynamically adjusting the negative conditioning strength during the generation process. This node is particularly useful for fine-tuning the influence of negative prompts, which can help in achieving more refined and controlled outputs. By leveraging advanced dynamic CFG (Classifier-Free Guidance) techniques, this node allows you to specify the strength of the negative conditioning, providing a more nuanced control over the model's behavior. The primary goal of this node is to offer a flexible and powerful tool for AI artists to manipulate the negative aspects of their prompts, leading to more precise and desirable results.

Automatic CFG - Negative Input Parameters:

model

This parameter represents the AI model that will be modified by the node. It is essential for the node to function as it provides the base model on which the adjustments will be applied.

boost

This boolean parameter determines whether to skip unconditional guidance during the process. When set to True, it can help in enhancing the model's performance by focusing more on the conditional aspects. The default value is True.

negative_strength

This float parameter controls the strength of the negative conditioning applied to the model. It allows you to fine-tune the influence of negative prompts, with a range from 0.0 to 5.0. The default value is 1.0, and it can be adjusted in steps of 0.1. A higher value increases the impact of the negative conditioning, while a lower value reduces it.

Automatic CFG - Negative Output Parameters:

model

The output is the modified AI model with the applied negative conditioning adjustments. This model will have the specified negative strength and other configurations set during the input phase, allowing for more controlled and refined outputs.

Automatic CFG - Negative Usage Tips:

• Experiment with different values of negative_strength to find the optimal balance for your specific use case. A higher value can help in scenarios where stronger negative guidance is needed.
• Utilize the boost parameter to skip unconditional guidance when you want the model to focus more on the conditional prompts, which can be particularly useful in complex generation tasks.

Automatic CFG - Negative Common Errors and Solutions:

"Model not provided"

• Explanation: This error occurs when the model parameter is not supplied.
• Solution: Ensure that you provide a valid AI model as input to the node.

"Invalid negative_strength value"

• Explanation: This error happens when the negative_strength value is outside the allowed range (0.0 to 5.0).
• Solution: Adjust the negative_strength value to be within the specified range of 0.0 to 5.0.

"Boost parameter missing"

• Explanation: This error indicates that the boost parameter is not provided.
• Solution: Make sure to include the boost parameter in your input, setting it to either True or False based on your requirements.