In this lesson, let's learn how to use ktrain to build a document answering model. We know that in document answering, we will have a set of documents, and we use those documents to answer a question. Let's see how we can do this using ktrain.

First, let's import the necessary libraries:

Before We Start

Starting Off with BERT

A Primer on Transformers

Understanding the BERT Model

Getting Hands-On with BERT

Exploring BERT Variants

Different BERT Variants

BERT Variants—Based on Knowledge Distillation

Applications of BERT

Exploring BERTSUM for Text Summarization

Semantic Search with Transformers

Applying BERT to Other Languages

Exploring Sentence and Domain-Specific BERT

Working with VideoBERT, BART, and More

Conclusion

Similarity Detection in English Language Using RoBERTa

Building a Document Answering Model