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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -85,7 +85,7 @@ The **Transformer model** architecture has revolutionized Natural Language Proce

### Core Components

1. **Encoder-Decoder Structure**: The original Transformer featured separate encoders for processing input sequences and decoders for generating outputs. However, variants like GPT (Generative Pre-trained Transformer) use **only the encoder** for tasks such as language modeling.
1. **Encoder-Decoder Structure**: The original Transformer featured separate encoders for processing input sequences and decoders for generating outputs. However, variants like GPT (Generative Pre-trained Transformer) use **only the decoder** for tasks such as language modeling.

2. **Self-Attention Mechanism**: This allows the model to weigh different parts of the input sequence when processing each element, forming the core of both encoder and decoder.

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