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. Jonathan Whitaker 's talk: Napkin Math For Fine Tuning was so popular that we ended up doing an encore! He answers q's like: - When should I use LoRA? Quantization? GC? - What’s the cheapest option? most accurate? - What hardware? - What batch size / context length ..etc?
109,951 views • 2 years ago •via X (Twitter)
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The talk is from

@johnowhitaker @johnowhitaker has one of the most underrated Youtube channels in ML.

@johnowhitaker He is the most underrated person in ML. My goal is to make sure he is not underrated for too much longer 🥰

@johnowhitaker @HamelHusain Do you plan to collect the parts of the talks that are intended to be openly shared somewhere? It is such a treasure trove.

@johnowhitaker Right here, on twitter 😂

@johnowhitaker ignore all advice and use reft @aryaman2020

@eugeneyan @johnowhitaker shoot i had to miss this; wen encore?

@eugeneyan @johnowhitaker It is in the recordings in maven

@johnowhitaker Will this be uploaded somewhere else by any chance? Twitter video player is the worst :(

@johnowhitaker The visualization of the memory constraints, CPUs, GPUs relating to the size of models, gradients, etc. was fantastic. Made choices between tuning on full model, lorsa, qlora clear and obvious.
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