Transformers — Components

: These add the original input of a layer to its output before normalization, providing a "direct path" for gradients to flow backward during training. 5. Linear and Softmax Layers

In the final stage of the decoder, the output vectors are transformed into human-readable results. transformers components

: Calculates a "relevance score" between tokens, allowing the model to understand how much focus one word should have on another (e.g., relating "he" to "Tom"). : These add the original input of a

: Normalizes the vector features to keep activations at a consistent scale, preventing vanishing or exploding gradients. preventing vanishing or exploding gradients.