Browse deepinfra models:
All categories and models you can try out and directly use in deepinfra:
Category/text-to-image
Text-to-image AI models are a powerful technology that can generate images based on textual descriptions, making them an essential tool for content creation, assistive technology, entertainment, and education.
The text description is first processed by a natural language processing (NLP) model, which extracts relevant features and keywords. This information is then passed to a generative model, which uses trained parameters to generate an image that matches the textual description. This innovative technology has the potential to transform visual content creation, making it more accessible and user-friendly.
For marketing and advertising professionals, text-to-image AI models can help create images that are tailored to specific campaigns or target audiences. Visually impaired individuals can use these models to better understand and interact with their environment, making them a valuable assistive technology. The entertainment industry can use text-to-image models to generate images for video games, virtual reality, and other immersive experiences. Finally, educators can use text-to-image models to create interactive diagrams, charts, and other resources to help students better understand complex concepts.
text-to-image
SDXL consists of an ensemble of experts pipeline for latent diffusion: In a first step, the base model is used to generate (noisy) latents, which are then further processed with a refinement model (available here: https://huggingface.co/stabilityai/stable-diffusion-xl-refiner-1.0/) specialized for the final denoising steps. Note that the base model can be used as a standalone module.
text-to-image
Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input.
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DreamShaper started as a model to have an alternative to MidJourney in the open source world. I didn't like how MJ was handled back when I started and how closed it was and still is, as well as the lack of freedom it gives to users compared to SD. Look at all the tools we have now from TIs to LoRA, from ControlNet to Latent Couple. We can do anything. The purpose of DreamShaper has always been to make "a better Stable Diffusion", a model capable of doing everything on its own, to weave dreams.
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The Deliberate Model allows for the creation of anything desired, with the potential for better results as the user's knowledge and detail in the prompt increase. The model is ideal for meticulous anatomy artists, creative prompt writers, art designers, and those seeking explicit content.
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Most widely used version of Stable Diffusion. Trained on 512x512 images, it can generate realistic images given text description
text-to-image
Stable Diffusion is a latent text-to-image diffusion model. Generate realistic images given text description
text-to-image
Stable diffusion with the ability to change checkpoint, still wip.
