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What is Transformer ?

A transformer is a deep learning architecture introduced in the paper "Attention Is All You Need" by Vaswani et al. It relies on self-attention mechanisms to process input data, making it highly effective for sequential and parallel tasks like natural language processing (NLP). Transformers eliminate the need for recurrent layers, enabling faster training and better handling of long-range dependencies in data. They are the foundation for models like BERT, GPT, and T5, excelling in applications such as translation, summarization, and text generation. The architecture uses encoder-decoder layers, attention mechanisms, and positional embeddings to process data efficiently.

Types of Transformer

Power Transformer

A power transformer is an electrical device used to transfer electrical energy between circuits at different voltage levels. It is primarily used in transmission networks to step up or step down voltage for efficient long-distance power distribution.

Auto Transformer

An auto transformer is a type of transformer that shares a common winding for both the primary and secondary circuits, unlike a traditional transformer where the primary and secondary windings are separate. It is used to step up or step down voltage and is often more compact and efficient for specific applications.

Three-Phase Transformer

A three-phase transformer is a type of transformer that is designed to handle three-phase electrical systems, which are commonly used for power transmission and distribution in industrial, commercial, and large residential setups. It is used to step up or step down voltage in three-phase systems to ensure efficient power distribution and usage.