Visit ComfyUI Online for ready-to-use ComfyUI environment
Enhance AI art generation with advanced text encoding for refined outputs and controlled results.
The Prompt With SDXL
node is designed to enhance your AI art generation process by integrating advanced text encoding techniques using the CLIPTextEncodeSDXL and CLIPTextEncodeSDXLRefiner classes. This node processes both positive and negative prompts, stripping away unnecessary syntax and encoding the text to create conditioning data that can be used to guide the AI model. By leveraging this node, you can achieve more refined and stylistically consistent outputs, as it allows for the inclusion of aesthetic scores and precise dimensions for both base and refiner models. This node is particularly beneficial for artists looking to fine-tune their prompts and achieve higher quality and more controlled results in their AI-generated artwork.
The positive_prompt
parameter is a string input that contains the text you want to positively influence the AI model's output. This prompt is processed and encoded to create conditioning data that guides the model towards generating images that align with the given positive description. There are no specific minimum or maximum values, but the prompt should be clear and descriptive to achieve the best results.
The negative_prompt
parameter is a string input that contains the text you want to negatively influence the AI model's output. This prompt is processed and encoded to create conditioning data that guides the model away from generating images that align with the given negative description. Similar to the positive prompt, there are no specific minimum or maximum values, but the prompt should be clear and descriptive to effectively steer the model.
The style
parameter is a string input that defines the stylistic approach to be applied to the prompts. In this node, the default value is set to 'none', meaning no additional style is applied. This parameter can be adjusted to include different styles if supported by the underlying model, allowing for more customized and varied outputs.
The seed
parameter is an integer input that ensures reproducibility of the results. By setting a specific seed value, you can generate the same output consistently, which is useful for fine-tuning and comparing different prompt configurations. The default value is typically set to a random number, but you can specify any integer value to control the randomness.
The width
parameter is an integer input that specifies the width of the generated image. This value is used to calculate the target dimensions for the base and refiner models. The default value is typically set to 1024, with a minimum value of 0 and a maximum value defined by the model's capabilities.
The height
parameter is an integer input that specifies the height of the generated image. Similar to the width parameter, this value is used to calculate the target dimensions for the base and refiner models. The default value is typically set to 1024, with a minimum value of 0 and a maximum value defined by the model's capabilities.
The sdxl_pos_cond
output parameter provides the conditioning data generated from the positive prompt. This data is used by the AI model to guide the generation process towards producing images that align with the positive description provided.
The sdxl_neg_cond
output parameter provides the conditioning data generated from the negative prompt. This data is used by the AI model to steer the generation process away from producing images that align with the negative description provided.
The refiner_pos_cond
output parameter provides the refined conditioning data generated from the positive prompt. This data is used by the refiner model to further enhance the quality and stylistic consistency of the generated images.
The refiner_neg_cond
output parameter provides the refined conditioning data generated from the negative prompt. This data is used by the refiner model to further steer the generation process away from producing images that align with the negative description provided.
The pos_prompt_
output parameter returns the processed positive prompt after stripping away unnecessary syntax. This cleaned prompt is used for encoding and generating conditioning data.
The neg_prompt_
output parameter returns the processed negative prompt after stripping away unnecessary syntax. This cleaned prompt is used for encoding and generating conditioning data.
seed
parameter to control the randomness and achieve reproducible results.width
and height
parameters to match the desired dimensions of your generated images.style
parameter if supported by the underlying model.width
and height
parameters to values within the supported range of the model.seed
parameter is set to an integer value to control the randomness effectively.© Copyright 2024 RunComfy. All Rights Reserved.