This is the last of a series of 3 videos where we demystify Transformer models and explain them with visuals and friendly examples.
Video 1: The attention mechanism in high level
Video 2: The attention mechanism with math
Video 3 (This one): Transformer models
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00:00 Introduction
01:50 What is a transformer?
04:35 Generating one word at a time
08:59 Sentiment Analysis
13:05 Neural Networks
18:18 Tokenization
19:12 Embeddings
25:06 Positional encoding
27:54 Attention
32:29 Softmax
35:48 Architecture of a Transformer
39:00 Fine-tuning
42:20 Conclusion
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