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Transformers — The NLP Revolution
In this blog post, we will explore the concept of Transformers in the field of Natural Language Processing (NLP). I will provide a brief overview of the history of Transformers, explain how they work, and discuss their impact on the field of NLP. By the end of this blog post, you will have a better understanding of how Transformers are being used in NLP and the potential implications of this technology.
Natural Language Processing, or NLP for short, is a subfield of artificial intelligence that focuses on enabling machines to understand, interpret, and manipulate human language. One of the most promising recent developments in the field of NLP is the use of Transformers, a novel neural network architecture that has achieved state-of-the-art results on many language-based tasks.
If you want an introduction about word processing before diving into Transformers, I wrote an article about this here.
Transformers were first introduced in a paper by researchers at Google in 2017, and they have since become widely used in NLP applications. The key advantage of Transformers over previous models is their ability to process input sequences of any length, allowing them to handle long-form text inputs such as entire articles or books. This is accomplished through the use of self-attention mechanisms, which allow the model to focus on different…
