Trying to choose a model/methodology (text generation)
Hello. I’m very new to NLP, though I’ve played around with Char-RNN and GPT-2 for text generation.The task I’m working on is a text generation one, and I’m trying to choose a model that will work for it. I’m trying to take a corpus of about 5 MB of emails and generate new emails that are similar in tone and subject matter. I’d like to run the generation “online” so that a user could visit a webpage and see a new generated email.Ideally, this is something that could run on CPU instead of GPU so I could use a low cost EC2 instance.I’d also like to use a model that could be “fine tuned” (I believe is the expression) to really capture again the tone and subject matter of the emails.My first attempt at this was using GPT-2 in a Google colab notebook where I generated 1000 examples and downloaded them, with the website being static and simply pulling one of the examples. However like I said, I’d really like to do this “online” so that the output is effectively endless.Thanks!