Machine-learning based generation of text style variations for digital content items

A non-transitory computer-readable storage medium storing computer program instructions executable to perform operations, the operations comprising:

• receiving, by an online system, a request including a reference content item, wherein the reference content item includes an image and a reference text that invites a viewer of the reference content item to perform a desired response;
• applying, by the online system, a machine-learned model to the reference text to generate a set of text variations corresponding to a set of text styles, wherein each text variation stylizes the textual content of the reference text in a respective text style in the set of text styles, wherein the machine-learned model includes an encoder and a set of decoders each assigned to a respective text style, and applying the machine-learned model further comprises:
• applying the encoder to an encoded version of the reference text to generate a text content embedding, the text content embedding characterizing textual content of the reference text, and
• for each decoder, applying the decoder to the text content embedding to generate a text variation that styles the reference text in the respective text style assigned to the decoder;
• generating, by the online system, a set of content item variations, each content item variation including the image and a respective text variation;
• and
• providing, to one or more client devices, the set of content item variations for display on one or more client devices.

A computer system comprising:

• a computer processor;
• and
• a non-transitory computer-readable storage medium storing computer program instructions executable to perform operations, the operations comprising:
• receiving, by an online system, a request including a reference content item, wherein the reference content item includes an image and a reference text that invites a viewer of the reference content item to perform a desired response;
• applying, by the online system, a machine-learned model to the reference text to generate a set of text variations corresponding to a set of text styles, wherein each text variation stylizes the textual content of the reference text in a respective text style in the set of text styles, wherein the machine-learned model includes an encoder and a set of decoders each assigned to a respective text style, and applying the machine-learned model further comprises:
• applying the encoder to an encoded version of the reference text to generate a text content embedding, the text content embedding characterizing textual content of the reference text, and
• for each decoder, applying the decoder to the text content embedding to generate a text variation that styles the reference text in the respective text style assigned to the decoder;
• generating, by the online system, a set of content item variations, each content item variation including the image and a respective text variation;
• and
• providing, to one or more client devices, the set of content item variations for display on one or more client devices.