🤖AI Summary
This article presents an updated and expanded version of a comprehensive guide to Transformer architecture improvements, building upon a 2020 post. The new version is twice the length and includes recent developments in Transformer models, providing detailed technical notations and covering both encoder-decoder and simplified architectures like BERT and GPT.
Key Takeaways
- →The updated Transformer Family guide is a superset of the 2020 version with approximately double the content length.
- →The article includes comprehensive mathematical notations for understanding Transformer architectures.
- →Coverage spans from vanilla Transformers to modern implementations including encoder-only BERT and decoder-only GPT models.
- →The guide represents three years of accumulated improvements and research in Transformer architectures.
- →The content serves as a technical reference for understanding the evolution of attention-based models.
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#transformer#architecture#deep-learning#bert#gpt#attention#neural-networks#nlp#machine-learning#technical-guide
Read Original →via Lil'Log (Lilian Weng)
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