LLMs and Transformers from Scratch: the Decoder | by Luís Roque

LLMs and Transformers from Scratch: the Decoder | by Luís Roque AI News, AI, AI tools, Innovation, itinai.com, LLM, Luís Roque, t.me/itinai, Towards Data Science - Medium **Exploring the Transformer’s Decoder Architecture: Practical Implementation and Value** *Introduction* In this article, we dive into the decoder component of the transformer architecture, highlighting its distinctive loop-like, iterative nature in contrast to the linear processing of the encoder. The decoder leverages masked multi-head attention and encoder-decoder multi-head attention mechanisms, and we showcase their practical implementation using Python and NumPy. *Practical Implementation* We demonstrate these concepts through a simple example of translating a sentence from English to Portuguese, offering a practical approach to illustrate the inner workings of the decoder in a transformer model. This provides a clearer understanding of its role in Large Language Models (LLMs). *Key Takeaways* - The decoder operates iteratively, utilizing attention mechanisms to process and generate new information. - Through a practical example, we illustrate how the decoder functions in a translation task, using Python and NumPy for implementation. *Practical AI Solutions* Discover how AI can revolutionize your company’s operations and maintain competitiveness. Identify Automation Opportunities, Define KPIs, Select an AI Solution, and Implement Gradually. Connect with us at [hello@itinai.com](mailto:hello@itinai.com) for AI KPI management advice and continuous insights into leveraging AI. Explore practical AI solutions at [itinai.com](https://itinai.com). *Useful Links* - [AI Lab in Telegram @aiscrumbot](https://t.me/aiscrumbot) – free consultation - [LLMs and Transformers from Scratch: the Decoder | by Luís Roque](Link to post on Towards Data Science – Medium) - Twitter – [@itinaicom](https://twitter.com/itinaicom) *References* References to the original paper and author are provided for further reading and exploration of the topic.