syuhmen

Maintainer: ferluht

Total Score

1

Last updated 5/17/2024
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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

The syuhmen model is a SDXL (Stable Diffusion XL) model fine-tuned on the paintings of syhmen. This model is maintained by ferluht, and shares some similarities with other SDXL-based models like sdxl-fresh-ink, sdxl-gta-v, and sdxl-inpainting.

Model inputs and outputs

The syuhmen model accepts a variety of inputs, including an image, a textual prompt, and options for controlling the output such as the width, height, and number of inference steps. The outputs are one or more generated images that match the provided prompt.

Inputs

  • Prompt: The textual description of the image to generate.
  • Negative Prompt: An optional textual description of what should not be included in the generated image.
  • Image: An optional input image that can be used for inpainting or img2img tasks.
  • Mask: An optional input mask for the inpainting task, where black areas will be preserved and white areas will be inpainted.
  • Seed: An optional random seed to ensure reproducibility of the generated images.
  • Width/Height: The desired dimensions of the output image.
  • Num Outputs: The number of images to generate.
  • Guidance Scale: The scale for classifier-free guidance, which affects the level of adherence to the provided prompt.
  • Num Inference Steps: The number of denoising steps to perform during the image generation process.

Outputs

  • Generated Images: One or more images matching the provided prompt.

Capabilities

The syuhmen model is capable of generating unique, high-quality images based on text prompts. It can produce a wide variety of styles and subjects, including fantastical and surreal elements. The model's fine-tuning on the artwork of syhmen gives it a distinct aesthetic that can be seen in the generated outputs.

What can I use it for?

The syuhmen model could be used for a variety of creative applications, such as generating art for personal or commercial use, creating illustrations for stories or games, or exploring unique artistic styles. The model's inpainting and img2img capabilities also make it useful for tasks like photo editing and restoration.

Things to try

One interesting aspect of the syuhmen model is its ability to capture the distinct style of the artist it was fine-tuned on. Try experimenting with different prompts to see how the model's outputs reflect this unique aesthetic. You could also explore the model's inpainting and img2img capabilities by providing input images and seeing how the model alters or enhances them.



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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