Uncommon

Text-to-image model

Machine learning model

Text-to-image model

Uncommon card · No. 182340

A text-to-image (T2I or TTI) model is a machine learning model which takes an input natural language prompt and produces an image matching that description. Text-to-image models gradually began to be developed in the mid-2010s during the beginnings of the AI boom, as a result of advances in deep neural networks. In 2022, the output of state-of-the-art text-to-image models—such as OpenAI's DALL-E 2, Google Brain's Imagen, Stability AI's Stable Diffusion, Midjourney, and Runway's Gen-4—began to be considered to approach the quality of real photographs and human-drawn art. Text-to-image models are generally latent diffusion models, which perform the diffusion process in a compressed latent space rather than directly in pixel space. An autoencoder (often a variational autoencoder) is used to convert between pixel space and this latent representation. These systems typically use a pretrained language or vision–language model to convert the input prompt into a text embedding, and a diffusion...

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