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Encode textual prompts for AI art generation, fine-tuning input for accurate and contextually relevant artwork.
The Zuellni IF Encode node is designed to process and encode textual prompts into a format that can be utilized by AI models for generating art. This node takes in both positive and negative prompts, which are then encoded using a specified model. The primary goal of this node is to transform user-provided textual descriptions into encoded representations that can guide the AI in creating more accurate and contextually relevant artwork. By leveraging this node, you can fine-tune the input prompts to better control the output of the AI model, ensuring that the generated art aligns closely with your creative vision.
This parameter specifies the model to be used for encoding the prompts. The model should be of type S0_MODEL
. The choice of model can significantly impact the quality and style of the encoded prompts, thereby influencing the final output of the AI-generated art.
This parameter is a string input where you can provide the positive prompt. The positive prompt is a textual description of the elements or themes you want to be prominently featured in the generated artwork. It supports multiline input, allowing for detailed and complex descriptions. The default value is an empty string.
This parameter is a string input where you can provide the negative prompt. The negative prompt is a textual description of the elements or themes you want to avoid or minimize in the generated artwork. It also supports multiline input, enabling you to specify detailed constraints. The default value is an empty string.
This output parameter contains the encoded representation of the positive prompt. It is used by the AI model to understand and incorporate the desired elements and themes into the generated artwork.
This output parameter contains the encoded representation of the negative prompt. It helps the AI model to recognize and avoid the specified elements and themes, ensuring that the generated artwork aligns with your constraints.
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