Transformers are used for translation and text summarising tasks because they can analyze sequential input data, such as natural language. Transformers use the self-attention process and weights the importance of each component of the input data differently. Large-scale transformer-based language models have gained a lot of popularity recently in the disciplines of computer vision and natural language processing (NLP).
They expand in size and complexity frequently, yet it…
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