But what is a GPT? Visual intro to transformers | Chapter 5, Deep Learning
Unpacking how large language models work under the hood
Early view of the next chapter for patrons:
Special thanks to these supporters: #thanks
To contribute edits to the subtitles, visit
Other recommended resources on the topic.
Richard Turner’s introduction is one of the best starting places:
Coding a GPT with Andrej Karpathy
Introduction to self-attention by John Hewitt
History of language models by Brit Cruise:
Paper about examples like the “woman - man” one presented here:
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Timestamps
0:00 - Predict, sample, repeat
3:03 - Inside a transformer
6:36 - Chapter layout
7:20 - The premise of Deep Learning
12:27 - Word embeddings
18:25 - Embeddings beyond words
20:22 - Unembedding
22:22 - Softmax with temperature
26:03 - Up next
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These animations are largely made using a custom Python library, manim. See the FAQ comments here:
#manim
All code for specific videos is visible here:
The music is by Vincent Rubinetti.
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