Introduction

I am amazed with the power of the T5 transformer model! T5 which stands for text to text transfer transformer makes it easy to fine tune a transformer model on any text to text task. Any NLP task event if it is a classification task, can be framed as an input text to output text problem.

In this blog, I show how you can tune this model on any data set you have. In particular, I demo how this can be done on Summarization data sets. I have personally tested this on CNN-Daily Mail and the WikiHow data sets. The code is publicly available on my Github here.

T5-small trained on Wikihow writes amazing summaries. See snippet below of actual text, actual summary and predicted summary. This model is also available on HuggingFace Transformers model hub here. The link provides a convenient way to test the model on input texts as well as a JSON endpoint.

#data-science #pytorch #nlp #machine-learning #artificial-intelligence