Transformers like BERT and GPT are powerful for specific applications. ... In tasks like translation, transformers manage context from past and future input using an encoder-decoder structure.

But not all transformer applications require both the encoder and decoder module. For example, the GPT family of large language models uses stacks of decoder modules to generate text.

Large language models (LLMs) such as GPT-4o, ... Google released bidirectional encoder representations from transformers (BERT), ... a transformer model follows an encoder-decoder architecture.

Pro What is BERT? Pro What are ... The most famous example of this is the generative pre-trained transformer (GPT) ... the encoder, the decoder and the attention mechanism.

Google itself leveraged the Transformer architecture to create BERT (Bidirectional Encoder Representations from Transformers). BERT drastically improved the way machines understood language ...

BERT-GPT, an encoder-decoder architecture, ... In experiments post-training, the Transformer, GPT, and BERT-GPT models were tested against common metrics for evaluating machine translation, ...

BERT stands for Bidirectional Encoder Representations from Transformers. ... following OpenAI's GPT-1. OpenAI's Generative Pre-trained Transformer 1 used Google's 2017 AI transformer concept. BERT ...

As such, GPT-3’s mathematical descriptions of the way we piece English together works whether we are writing columns or coding software programs. Using these maps, GPT-3 can perform tasks it was ...