zxuu/Self-Attention
Transformer的完整实现。详细构建Encoder、Decoder、Self-attention。以实际例子进行展示，有完整的输入、训练、预测过程。可用于学习理解self-attention和Transformer
This project offers a hands-on implementation of the Transformer neural network architecture, specifically focusing on its self-attention mechanism. It takes paired sequences of text, such as a sentence in one language and its translation, and processes them to demonstrate how Transformers can learn to generate one sequence from another. This is for machine learning engineers or researchers who want to understand the inner workings of Transformers and self-attention.
127 stars. No commits in the last 6 months.
Use this if you are a machine learning engineer or researcher looking for a complete, working example to learn and understand the Transformer architecture and its self-attention components in detail.
Not ideal if you are a practitioner looking for a pre-trained model or a high-level API to directly apply Transformers to your own data without needing to understand the underlying implementation.
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Python
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Last pushed
Apr 10, 2025
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