kyegomez/AoA-torch
Implementation of Attention on Attention in Zeta
This project provides an implementation of the Attention on Attention (AoA) mechanism, a component used in advanced deep learning models. It takes an input sequence of data (like numerical representations of text or images) and processes it to produce an output sequence with enhanced contextual understanding. This is useful for researchers and practitioners building custom neural networks, particularly in areas like computer vision or natural language processing, who need to integrate specific attention mechanisms.
Available on PyPI.
Use this if you are a machine learning researcher or engineer designing and experimenting with custom deep learning architectures that require a specific attention mechanism for improved performance.
Not ideal if you are a casual user looking for an out-of-the-box solution to a specific problem without needing to build or modify neural network components.
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5
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Language
Python
License
MIT
Category
Last pushed
Feb 16, 2026
Commits (30d)
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