Congratulations! We have made it to the final chapter. We have come a long way. We started off with understanding transformers, then we learned about BERT and several different variants of BERT in detail, from ALBERT to SentenceBERT. In this chapter, we will learn about two interesting models named VideoBERT and BART. We will also explore two popular BERT libraries known as ktrain and bert-as-service. We will start off the chapter by learning how VideoBERT works. We will look at how the VideoBERT model is pre-trained to learn the representation of language and video in a joint manner. Then, we will look into some of the applications of VideoBERT.
Moving on, we will learn what BART is and how it differs from the BERT model. We will understand the different noising techniques used in BART in detail. Then, we will see how to perform text summarization...
