Greetings to everyone,
I want to design a system that is able to generate stories or poetry based on a large dataset of text, without being needed to feed a text description/start/summary as input at inference time.
So far I did this using RNN 's, but as you know they have a lot of flaws. My question is, what are the best methods to achieve this task at the time? I searched for possibilities using Attention mechanisms , but it turns out that they are fitted for translation tasks.
P.S. I know about GPT-2, Bert, Transformer , etc., but all of them need a text description as input, before the generation and this is not what I’m seeking. I want a system able to generate stories from scratch after training.
Thanks a lot!