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DeepFloyd IF

Developed by DeepFloyd Lab at Stability AI, DeepFloyd IF is a state-of-the-art open-source text-to-image model that excels in photorealism and language comprehension. It employs a modular architecture comprising a frozen text encoder and three cascaded pixel diffusion modules. The process begins with a base model generating a 64x64 pixel image from a text prompt, followed by two super-resolution models that upscale the image to 256x256 and 1024x1024 pixels, respectively. This design enables the creation of high-quality images that accurately reflect complex textual descriptions. DeepFloyd IF has demonstrated superior performance, achieving a zero-shot FID score of 6.66 on the COCO dataset, underscoring its potential for advancing text-to-image synthesis.