Decoder-Only Transformers, ChatGPTs specific Transformer, Clearly Explained!!!
Transformers are taking over AI right now, and quite possibly their most famous use is in ChatGPT. ChatGPT uses a specific type of Transformer called a Decoder-Only Transformer, and this StatQuest shows you how they work, one step at a time. And at the end (at 32:14), we talk about the differences between a Normal Transformer and a Decoder-Only Transformer. BAM! NOTE: If you're interested in learning more about Backpropagation, check out these 'Quests: The Chain Rule: • The Chain Rule, Clearly Explained!!! Gradient Descent: • Gradient Descent, Step-by-Step Backpropagation Main Ideas: • Neural Networks Pt. 2: Backpropagation Mai... Backpropagation Details Part 1: • Backpropagation Details Pt. 1: Optimizing ... Backpropagation Details Part 2: • Backpropagation Details Pt. 2: Going bonke... If you're interested in learning more about the SoftMax function, check out: • Neural Networks Part 5: ArgMax and SoftMax If you're interested in learning more about Word Embedding, check out: • Word Embedding and Word2Vec, Clearly Expla... If you'd like to learn more about calculating similarities in the context of neural networks and the Dot Product, check out: Cosine Similarity: • Cosine Similarity, Clearly Explained!!! Attention: • Attention for Neural Networks, Clearly Exp... If you'd like to learn more about Normal Transformers, see: • Transformer Neural Networks, ChatGPT's fou... For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Patreon: / statquest ...or... YouTube Membership: / @statquest ...buying one of my books, a study guide, a t-shirt or hoodie, or a song from the StatQuest store... https://statquest.org/statquest-store/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: / joshuastarmer 0:00 Awesome song and introduction 1:34 Word Embedding 7:26 Position Encoding 10:10 Masked Self-Attention, an Autoregressive method 22:35 Residual Connections 23:00 Generating the next word in the prompt 26:23 Review of encoding and generating the prompt 27:20 Generating the output, Part 1 28:46 Masked Self-Attention while generating the output 30:40 Generating the output, Part 2 32:14 Normal Transformers vs Decoder-Only Transformers #StatQuest
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