Overview
Transformers are a type of deep learning model that have revolutionized natural language processing. They work by using attention mechanisms to process data in parallel, making them faster and more efficient than previous models. This introduction will cover the basic concepts of transformers, how they function, and their applications in various fields such as text generation and translation.
📚 Key Learning Objectives
- ✓ Explain the basic structure of a transformer model.
- ✓ Identify key components like attention and encoder-decoder.
- ✓ Describe how transformers differ from traditional models.
- ✓ Apply transformers to simple natural language tasks.
- ✓ Evaluate the performance of a transformer model.
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