warner-benjamin/commented-transformers
Highly commented implementations of Transformers in PyTorch
This project provides fully explained, from-scratch implementations of advanced machine learning models like GPT-2 and BERT. It helps deep learning practitioners understand the inner workings of Transformer architectures by showing detailed PyTorch code for components like attention mechanisms. If you're learning how to build these models from the ground up, you'll find clear, line-by-line explanations.
138 stars. No commits in the last 6 months.
Use this if you are a deep learning student or researcher who wants to learn the fundamental components and full architecture of Transformer models through commented PyTorch code.
Not ideal if you're looking for a high-level library to quickly apply pre-trained Transformer models without needing to understand their internal structure.
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138
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8
Language
Python
License
MIT
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Last pushed
Aug 02, 2023
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