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[R]eading List for Andrej Karpathy’s “Busy person’s intro to Large Language Models” Video (alien.top)

submitted 10 months ago by FallMindless3563@alien.top to c/machinelearning@academy.garden

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I loved Andrej’s talk about in his “Busy person’s intro to Large Language Models” video, so I decided to create a reading list to dive in deeper to a lot of the topics. I feel like he did a great job of describing the state of the art for anyone from an ML Researcher to any engineer who is interested in learning more.

The full talk can be found here: https://youtu.be/zjkBMFhNj_g?si=fPvPyOVmV-FCTFEx

Here’s the reading list: https://blog.oxen.ai/reading-list-for-andrej-karpathys-intro-to-large-language-models-video/

Let me know if you have any other papers you would add!

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[–] um-xpto@alien.top 1 points 10 months ago (3 children)

Nice! Thank you for your work.

Regarding the video.

Q1) minute 14:14 Finetuning into an Assistant, when you have multiple tasks / datasets with diverse outputs how is training performed ? Are all datasets combined in a single training ? Or Is finetuning done over a previous finetuning ? Or the question is parsed and sent to a specific model ?

Q2) minute 27:43 Tool Use (Browser, Calculator, etc. ) Anyone has links for similar implementations for llama and how is done or what kind of tech/frameworks are used ?

[–] FallMindless3563@alien.top 1 points 10 months ago

You certainly can combine all the tasks and datasets into a single instruction fine tuning dataset. Then you would have a separate dataset for the reinforcement learning half where the model is learning human preferences.

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