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An image conditioned on the prompt an astronaut riding a horse, by Hiroshige, generated by Stable Diffusion 3.5, a large-scale text-to-image model first released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.
Diagram of the latent diffusion architecture used by Stable Diffusion The denoising process used by Stable Diffusion. The model generates images by iteratively denoising random noise until a configured number of steps have been reached, guided by the CLIP text encoder pretrained on concepts along with the attention mechanism, resulting in the desired image depicting a representation of the ...
Stable Diffusion, prompt a photograph of an astronaut riding a horse Producing high-quality visual art is a prominent application of generative AI. [ 53 ] Generative AI systems trained on sets of images with text captions include Imagen , DALL-E , Midjourney , Adobe Firefly , FLUX.1 , Stable Diffusion and others (see Artificial intelligence art ...
For AI art generation, which generates images from text prompts, NovelAI uses a custom version of the source-available Stable Diffusion [2] [14] text-to-image diffusion model called NovelAI Diffusion, which is trained on a Danbooru-based [5] [1] [15] [16] dataset. NovelAI is also capable of generating a new image based on an existing image. [17]
An image conditioned on the prompt an astronaut riding a horse, by Hiroshige, generated by Stable Diffusion 3.5, a large-scale text-to-image model first released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.
AI technology is becoming more widely available, such as stable diffusion (open-source technology that can produce images from text prompts) and “face-swap” tools that can put a victim’s ...
Stable Diffusion, for example, imposes conditioning in the form of cross-attention mechanism, where the query is an intermediate representation of the image in the U-Net, and both key and value are the conditioning vectors. The conditioning can be selectively applied to only parts of an image, and new kinds of conditionings can be finetuned ...
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