Introduction

• In this section we will:
  • Learn the basic building blocks of a Transformer model.
  • Learn what makes up a tokenization pipeline.
  • See how to use a Transformer model in practice.
  • Learn how to leverage a tokenizer to convert text to tensors that are understandable by the model.
  • Set up a tokenizer and a model together to get from text to predictions.
  • Learn the limitations of input IDs, and learned about attention masks.
  • Play around with versatile and configurable tokenizer methods.