Transformers Models

Transformers models are a class of deep learning models primarily used in natural language processing tasks. They are based on the transformer architecture, which uses self-attention mechanisms to process sequential data, such as text, more effectively than previous models like RNNs and LSTMs.

How Transformers Models Work

Transformers models are particularly adept at handling tasks involving long-range dependencies and context understanding in text. They are the underlying technology for many state-of-the-art language models, like GPT (Generative Pre-trained Transformer) and BERT (Bidirectional Encoder Representations from Transformers), which have revolutionized natural language understanding and generation tasks.