Generating content based on text and supplemental information

A computer-implemented method, comprising:

• receiving, from a client device associated with a user, a text input;
• receiving a supplemental information embedding vector associated with the user, the supplemental information embedding vector comprising user interactions with respective content items;
• providing the text input and the supplemental information embedding to a machine learning model trained to generate a rendered image based at least in part on the text input and the supplemental information embedding, the machine learning model trained based on a training dataset comprising triplets of data for a plurality of users, one or more respective triplets of data comprising a training text string submitted by a corresponding user, a training image submitted by the corresponding user, and training supplemental information comprising a user embedding vector representative of the corresponding user;
• generating, by the machine learning model, the rendered image;
• and
• providing the rendered image to the client device in response to the text input.

A computer-implemented method, comprising:

• training, using a plurality of training data sets, a machine learning model to generate an image based at least in part on an input text string and a plurality of content items, wherein one or more of the plurality of training data sets includes triplets of data for a plurality of users, one or more triplets of data comprising a training text string submitted by the first user, a training image engaged with by the first user in response to the text input, and a training collection of content items, wherein the training image belongs to the training collection of content items;
• receiving, at the trained machine learning model, a text input provided by a second user;
• receiving, at the trained machine learning model, a plurality of example content items provided by the second user that form at least a portion of a collection of content items;
• generating, using the trained machine learning model and based at least in part on the text input and the plurality of example content items, a rendered image;
• and
• providing, in response to the text input, the rendered image.