knotgrass/attention
several types of attention modules written in PyTorch for learning purposes
This project helps machine learning researchers and students understand how different 'attention' mechanisms work within neural networks. It takes sequential data and processes it using various attention modules, outputting how different parts of the input are weighted and combined. It's designed for those learning about or experimenting with foundational AI model architectures.
Use this if you are a machine learning student or researcher looking to study and understand the core mechanics of various attention modules from a simple, unoptimized implementation.
Not ideal if you need high-performance, optimized attention modules for large-scale AI model training or deployment, as this version is for educational purposes.
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Python
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Last pushed
Jan 02, 2026
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