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Enhance AI art conditioning by sculpting text embeddings for precise artistic control.
The CLIP Vector Sculptor text encode node is designed to enhance the conditioning process in AI art generation by manipulating the text embeddings produced by the CLIP model. This node allows you to sculpt the vector representations of text inputs, providing more control over how the text influences the generated art. By adjusting the intensity, method, and normalization of the sculpting process, you can fine-tune the conditioning to achieve desired artistic effects. This node is particularly useful for artists looking to experiment with different text conditioning techniques to create unique and expressive AI-generated artworks.
This parameter represents the CLIP model used for encoding the text. The CLIP model is responsible for converting the text input into vector embeddings that can be manipulated by the sculptor.
This is the text input that you want to encode and manipulate. It can be a single line or multiline string, allowing for complex and detailed descriptions. The text input serves as the basis for generating the initial vector embeddings.
This parameter controls the intensity of the sculpting process. It is a floating-point value with a default of 1, a minimum of 0, and a maximum of 10, adjustable in steps of 0.01. Higher values result in more pronounced modifications to the text embeddings, while lower values result in subtler changes.
This parameter determines the method used for sculpting the text embeddings. The available options are "forward", "backward", "maximum_absolute", and "add_minimum_absolute". Each method applies a different technique to modify the embeddings, affecting the final conditioning in unique ways.
This parameter specifies the normalization technique applied to the token embeddings. The available options are "none", "mean", "set at 1", "default * attention", "mean * attention", "set at attention", and "mean of all tokens". Normalization helps in controlling the magnitude and distribution of the embeddings, ensuring consistent and predictable results.
This output contains the conditioned embeddings generated by the CLIP model after applying the sculpting process. These embeddings are used to influence the AI art generation process, guiding the model to produce images that align with the sculpted text input.
This output provides a string representation of the parameters used in the sculpting process. It includes the intensity, method, and normalization settings, allowing you to keep track of the configuration used for each conditioning. If the sculptor intensity is set to 0 and token normalization is "none", this output will indicate that the sculpting is disabled.
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