Repo for implementations of various Transformer Attn mechanisms

📰 Analysis

A GitHub repository has been created to implement various Transformer attention mechanisms. The repository provides a collection of code for different attention mechanisms, including multi-head attention, self-attention, and relative attention. This repository is useful for AI/ML practitioners who want to experiment with different attention mechanisms and understand their implementation details. The Transformer architecture has been widely adopted in NLP tasks, and attention mechanisms are a key component of this architecture. By exploring different attention mechanisms, developers can improve the performance of their models and gain a deeper understanding of the Transformer architecture.