Core Implementation

Now comes the exciting part: implementing the Transformer model. We will start with the basic building blocks.

The Self-Attention Mechanism

At the heart of the Transformer is the self-attention mechanism. This allows the model to weigh the importance of different words in a sentence relative to each other.

import torch
import torch.nn as nn

class SelfAttention(nn.Module):
    def __init__(self, embed_size, heads):
        super(SelfAttention, self).__init__()
        # ... implementation details ...

We will continue building the Multi-Head Attention, Feed-Forward Network, and finally assemble the full Transformer block.