sdxl-tron

Maintainer: fofr

Total Score

11

Last updated 6/11/2024
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Model LinkView on Replicate
API SpecView on Replicate
Github LinkNo Github link provided
Paper LinkNo paper link provided

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Model overview

sdxl-tron is a fine-tuned SDXL (Stable Diffusion XL) model based on the Tron Legacy film. It was created by fofr, who has also developed similar models like [object Object], [object Object], [object Object], [object Object], and [object Object]. These models explore different fine-tuning approaches and artistic styles.

Model inputs and outputs

sdxl-tron is a versatile model that can be used for text-to-image generation, image-to-image translation, and inpainting. The model accepts a range of inputs, including a prompt, an optional input image, a mask for inpainting, and various parameters to control the output. The outputs are high-quality images that reflect the Tron Legacy aesthetic.

Inputs

  • Prompt: The text prompt that describes the desired image.
  • Image: An optional input image for image-to-image translation or inpainting.
  • Mask: A mask for inpainting, where black areas will be preserved and white areas will be inpainted.
  • Width and Height: The desired dimensions of the output image.
  • Seed: A random seed, which can be left blank to randomize the output.
  • Refine: The refine style to use, such as "no_refiner" or "expert_ensemble_refiner".
  • Scheduler: The scheduler to use, such as DDIM.
  • LoRA Scale: The additive scale for the LoRA (Low-Rank Adaptation) component.
  • Num Outputs: The number of images to generate.
  • Refine Steps: The number of steps to refine the output for the "base_image_refiner".
  • Guidance Scale: The scale for classifier-free guidance.
  • Apply Watermark: A boolean to enable or disable the application of a watermark.
  • High Noise Frac: The fraction of noise to use for the "expert_ensemble_refiner".
  • Negative Prompt: An optional negative prompt to guide the generation.
  • Prompt Strength: The strength of the prompt when using image-to-image or inpainting.
  • Num Inference Steps: The number of denoising steps to perform.

Outputs

  • Images: The generated image(s) in the form of image URIs.

Capabilities

sdxl-tron is capable of generating high-quality, Tron Legacy-inspired images. The model can create a wide range of scenes, from futuristic cityscapes to surreal digital landscapes, all with the distinctive visual style of the Tron universe. This model could be particularly useful for visual effects, game design, or any project that requires a distinctive, cyberpunk-inspired aesthetic.

What can I use it for?

You can use sdxl-tron for a variety of creative projects, such as generating concept art for a science fiction or cyberpunk-themed game, creating promotional materials or cover art for a Tron-inspired book or film, or even producing unique digital artwork for personal or commercial use. The versatility of the model's inputs and outputs makes it a powerful tool for visual artists and designers.

Things to try

One interesting aspect of sdxl-tron is its ability to blend the Tron Legacy aesthetic with other visual styles. Try experimenting with different prompts that combine Tron-inspired elements with other genres, such as fantasy, horror, or retro-futurism. You can also explore the model's inpainting capabilities by providing input images and masks to see how it can seamlessly integrate new Tron-themed elements into existing scenes.



This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!

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