coreml-stable-diffusion-xl-base
Maintainer: apple - Last updated 5/28/2024
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Model overview
The coreml-stable-diffusion-xl-base model is a text-to-image generation model developed by Apple. It is based on the Stable Diffusion XL (SDXL) model, which consists of an ensemble of experts pipeline for latent diffusion. The base model generates initial noisy latents, which are then further processed with a refinement model to produce the final denoised image. Alternatively, the base model can be used on its own in a two-stage pipeline to first generate latents and then apply a specialized high-resolution model for the final image.
Model inputs and outputs
The coreml-stable-diffusion-xl-base model takes text prompts as input and generates corresponding images as output. The text prompts can describe a wide variety of scenes, objects, and concepts, which the model then translates into visual form.
Inputs
- Text prompt: A natural language description of the desired image, such as "a photo of an astronaut riding a horse on mars".
Outputs
- Generated image: The model outputs a corresponding image based on the input text prompt.
Capabilities
The coreml-stable-diffusion-xl-base model is capable of generating high-quality, photorealistic images from text prompts. It can create a wide range of scenes, objects, and concepts, and performs significantly better than previous versions of Stable Diffusion. The model can also be used in a two-stage pipeline with a specialized high-resolution refinement model to further improve image quality.
What can I use it for?
The coreml-stable-diffusion-xl-base model is intended for research purposes, such as the generation of artworks, applications in educational or creative tools, and probing the limitations and biases of generative models. The model should not be used to create content that is harmful, offensive, or misrepresents people or events.
Things to try
Experiment with different text prompts to see the variety of images the model can generate. Try combining the base model with the stable-diffusion-xl-refiner-1.0 model to see if the additional refinement step improves the image quality. Explore the model's capabilities and limitations, and consider how it could be applied in creative or educational contexts.
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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