gazelle93/Attention-Various-Positional-Encoding
This project aims to implement the Scaled-Dot-Product Attention layer and the Multi-Head Attention layer using various Positional Encoding methods.
This is a tool for developers building natural language processing (NLP) models. It helps in implementing attention layers, a core component in modern language models, by offering different methods for positional encoding. Developers can input text and configure attention types and positional encoding schemes to get attention scores, which are crucial for model performance in various NLP tasks.
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Use this if you are an NLP developer experimenting with different attention mechanisms and positional encoding techniques for your language models.
Not ideal if you are an end-user looking for a ready-to-use NLP application or a library for general text processing tasks.
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Python
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Jun 27, 2022
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