hasdx

Maintainer: cjwbw

Total Score

29

Last updated 6/12/2024
AI model preview image
PropertyValue
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 hasdx model is a mixed stable diffusion model created by cjwbw. This model is similar to other stable diffusion models like stable-diffusion-2-1-unclip, stable-diffusion, pastel-mix, dreamshaper, and unidiffuser, all created by the same maintainer.

Model inputs and outputs

The hasdx model takes a text prompt as input and generates an image. The input prompt can be customized with parameters like seed, image size, number of outputs, guidance scale, and number of inference steps. The model outputs an array of image URLs.

Inputs

  • Prompt: The text prompt that describes the desired image
  • Seed: A random seed to control the output image
  • Width: The width of the output image, up to 1024 pixels
  • Height: The height of the output image, up to 768 pixels
  • Num Outputs: The number of images to generate
  • Guidance Scale: The scale for classifier-free guidance
  • Negative Prompt: Text to avoid in the generated image
  • Num Inference Steps: The number of denoising steps

Outputs

  • Array of Image URLs: The generated images as a list of URLs

Capabilities

The hasdx model can generate a wide variety of images based on the input text prompt. It can create photorealistic images, stylized art, and imaginative scenes. The model's capabilities are comparable to other stable diffusion models, allowing users to explore different artistic styles and experiment with various prompts.

What can I use it for?

The hasdx model can be used for a variety of creative and practical applications, such as generating concept art, illustrating stories, creating product visualizations, and exploring abstract ideas. The model's versatility makes it a valuable tool for artists, designers, and anyone interested in AI-generated imagery. As with similar models, the hasdx model can be used to monetize creative projects or assist with professional work.

Things to try

With the hasdx model, you can experiment with different prompts to see the range of images it can generate. Try combining various descriptors, genres, and styles to see how the model responds. You can also play with the input parameters, such as adjusting the guidance scale or number of inference steps, to fine-tune the output. The model's capabilities make it a great tool for creative exploration and idea generation.



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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