How to deal with out of vocabulary words in nlp?

I have a multi-label dataset that contains a lot of out-of-vocabulary words. The dataset is basically from a user forum site. The columns are post_title, post_description and tags. I want to predict the tags using machine learning models. But as the dataset contains many out-of-vocabulary words, the models are giving me very poor results. So what should I do in this case?