This model is based on the smallest gpt2 model (137 M parameters) fine-tuned on the Gutenberg Poetry Corpus (142 MB of text) for 3 epochs.

The model generates lines of poetry, in English, each of them starting with the <start> tag, which can be removed through post-processing.

This model was trained by Teo Ferrari as part of his Bachelor thesis at HEIG-VD, supervised by Andrei Popescu-Belis. The model is described in "GPoeT: a Language Model Trained for Rhyme Generation on Synthetic Data" and is used in the CR-PO system for interactive poem generation, along with several other models for specific topics or emotions.