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New depth-guided stable diffusion model, finetuned from SD 2.0-base. The model is conditioned on monocular depth estimates inferred via MiDaS and can be used for structure-preserving img2img and shape-conditional synthesis.
Stable Diffusion 3 is an advanced text-to-image model designed to create detailed and realistic images based on user-generated text prompts. It leverages a diffusion transformer architecture and flow matching technology to enhance image quality and speed of generation, making it a powerful tool for artists, designers, and content creators.
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22 de fev. de 2024 · Announcing Stable Diffusion 3 in early preview, our most capable text-to-image model with greatly improved performance in multi-subject prompts, image quality, and spelling abilities.
Stable Diffusion is a text-to-image model that generates photo-realistic images given any text input. What makes Stable Diffusion unique ? It is completely open source. The model and the code that uses the model to generate the image (also known as inference code).
18 de out. de 2022 · Stable Diffusion is a latent diffusion model conditioned on the (non-pooled) text embeddings of a CLIP ViT-L/14 text encoder. We provide a reference script for sampling, but there also exists a diffusers integration, which we expect to see more active community development.
Stable Diffusion XL is an open-source AI image generation model designed to produce photorealistic images and improved representations of human anatomy. It is equipped with the capability to generate legible text within images, a notable advancement over previous models.
