Transformers have become a cornerstone in the field of deep learning, especially in natural language processing. This page provides a visual overview of how transformers work, along with resources to dive deeper into the topic.
Key Components of Transformers
- Encoder: Processes the input sequence and generates a sequence of internal representations.
- Decoder: Converts the internal representations back into the output sequence.
- Attention Mechanism: Allows the model to focus on different parts of the input sequence when generating each part of the output sequence.
Visualization
To better understand transformers, here's a visual representation of a transformer model:
Learn More
For an in-depth understanding of transformers, we recommend checking out the following resources:
By exploring these resources, you'll gain a comprehensive understanding of transformers and their applications.