In this chapter, we will learn how to use the pre-trained BERT model in detail. First, we will look at the different configurations of the pre-trained BERT model open sourced by Google. Then, we will learn how to use the pre-trained BERT model as a feature extractor. We will also explore Hugging Face's transformers library and learn how to use it to extract embeddings from the pre-trained BERT.
Moving on, we will understand how to extract embeddings from all encoder layers of BERT. Next, we will learn how to fine-tune the pre-trained BERT model for the downstream tasks. First, we will learn to fine-tune the pre-trained BERT model for a text classification task. Next, we will learn to fine-tune BERT for sentiment analysis tasks using the transformers library. Then, we will look into fine-tuning the pre-trained BERT model for natural language inference...
