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 nlp.seas.harvard.edu
The Annotated Transformer
| | swethatanamala.github.io
NLP - Attention Is All You Need ยท Swetha's Blog
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| | In this paper, authors proposed a new simple network architecture, the Transformer, based solely on attention mechanisms, removing convolutions and recurrences entirely. Transformer is the first transduction model relying entirely...
| | harvardnlp.github.io
The Annotated Transformer
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| | [AI summary] The provided code is a comprehensive implementation of the Transformer model, including data loading, model architecture, training, and visualization. It also includes functions for decoding and visualizing attention mechanisms across different layers of the model. The code is structured to support both training and inference, with examples provided for running the model and visualizing attention patterns.
| | jalammar.github.io
The Illustrated Transformer - Jay Alammar - Visualizing machine learning one concept at a time.
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| | Discussions: Hacker News (65 points, 4 comments), Reddit r/MachineLearning (29 points, 3 comments) Translations: Arabic, Chinese (Simplified) 1, Chinese (Simplified) 2, French 1, French 2, Italian, Japanese, Korean, Persian, Russian, Spanish 1, Spanish 2, Vietnamese Watch: MIT's Deep Learning State of the Art lecture referencing this post Featured in courses at Stanford, Harvard, MIT, Princeton, CMU and others Update: This post has now become a book! Check out LLM-book.com which contains (Chapter 3) an updated and expanded version of this post speaking about the latest Transformer models and how they've evolved in the seven years since the original Transformer (like Multi-Query Attention and RoPE Positional embeddings). In the previous post, we looked at Att...
| | golb.hplar.ch
Building a simple neural network with Java and JavaScript
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| [AI summary] The blog post details the author's experience implementing a feedforward neural network for digit recognition using Java and JavaScript, explaining the underlying algorithms, shared external libraries, and architectural decisions while reviewing an introductory book on the topic.