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The Transformer neural network architecture EXPLAINED. “Attention is all you need”
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🔗 Table of contents with links:
* 00:00 The Transformer
* 00:38 RNNs recap
* 01:14 Transformers high-level
* 02:27 The Transformer encoder
* 03:39 Self-attention compared to attention
* 04:51 Parallelisation
* 05:37 Encoding word order
* 06:13 Residual connections
* 06:35 Generating the output sequence
* 07:59 Masked word prediction
* 08:40 Self-supervised learning FTW!
* 09:08 Pre-training and fine-tuning and Probing
* 09:44 End dance ;)
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