Transformer Architecture Explained: Encoder, Decoder, and GPT's Approach

The Transformer architecture, introduced in the 2017 paper "Attention Is All You Need," is a foundational concept in modern AI, particularly for language models. It comprises an encoder and a decoder, though variations like encoder-only (BERT) and decoder-only (GPT) models exist. Text is first tokenized and converted into numerical embeddings, with positional information added to retain sequence order. The core mechanism is self-attention, allowing tokens to weigh the relevance of other tokens in the sequence to understand context. AI

IMPACT Provides a foundational understanding of how large language models like GPT process information.

RANK_REASON Detailed explanation of a foundational AI architecture and its variations. [lever_c_demoted from research: ic=1 ai=1.0]

Read on dev.to — LLM tag →

• Attention Is All You Need
• BERT
• GPT
• T5 Text To Text Transfer Transformer
• Transformer

• paper
• model release

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →