"DALL·E" is a model developed by OpenAI that generates images from textual descriptions. DALL·E combines both transformer and convolutional neural network (CNN) components.
The transformer architecture is used to process the textual input, allowing the model to understand and generate image descriptions. The transformer component is responsible for capturing the semantic relationships between words and learning the contextual information from the input text.
In addition to the transformer, DALL·E employs a decoder network that utilizes a variant of the autoregressive model, which includes recurrent neural network (RNN) components. The RNN helps generate the images pixel by pixel, incorporating both local and global context to create coherent and visually appealing images.
Therefore, DALL·E utilizes a combination of transformers and RNNs in its architecture to generate images based on textual descriptions. It leverages the strengths of both approaches to achieve its remarkable image generation capabilities.
