Oh, I hadn't realized that you meant that the embedding would contain information about other features, I get it now. I was referencing an RNN since I thought it was the only option due to the variable input size. Thanks
Yeah I'm gonna try both options (with BERT and the bigger models) but since I'm working with a big dataset I'm not sure I'll be able to use the larger models due to the token and request limits. Thanks for the help
But even then, with the other features (sentiment analysis, tf-idf) how would I feed a vector containing a varying number of tokens and other types of features? I can't see how you would this using an RNN. That is for each post
danilo62 OP t1_jefo88t wrote
Reply to comment by --dany-- in [D] Best deal with varying number of inputs each with variable size using and RNN? (for an NLP task) by danilo62
Oh, I hadn't realized that you meant that the embedding would contain information about other features, I get it now. I was referencing an RNN since I thought it was the only option due to the variable input size. Thanks