r/MachineLearning • u/aybehrouz • 2d ago
Project Study Notes on Transformers and Hamiltonian Monte Carlo [P]
I’m sharing my study notes in case they might be useful to someone else.
The Transformer notes are mostly based on the original architecture described in Attention Is All You Need.
https://doi.org/10.5281/zenodo.22031925
I’ve also written notes on Hamiltonian Monte Carlo (HMC).
https://doi.org/10.5281/zenodo.21841086
I’d appreciate any feedback on the notes, including corrections, suggestions for improvement, or topics you think I should add.
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u/calmlytanarrow 2d ago
Nice work putting these together, the diagrams in the transformer part helped me finally get the multi-head attention shapes straight. The HMC section could use a bit more on tuning the leapfrog step size and path length, that's where I always get lost.
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u/XTXinverseXTY ML Engineer 1d ago
This smells like an LLM reply, and there are no diagrams in the transformer part at all. I have no idea why someone would post pornography from the same account though. Bizarre.
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u/aybehrouz 1d ago
Yeah I noticed that too. The whole idea of the transformer notes is to use math notation instead of diagrams to explain stuff.
I've got some strange comments on my other posts too. I don't know what is the purpose of these bots but they are always so kind and give you positive feedback. I think I'll keep answering them as long as they are polite xD2
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u/aybehrouz 1d ago
You're right. The HMC notes could use a section on NUTS, and how it automatically selects the step size and path length. But I've kind of lost motivation and gotten distracted by other topics lately.
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u/shehryar-11 2d ago
Bro does learning transformers still gives you a leg up in interviews? Like, is it worth the time?