HackerA Hackers' Guide to Language Models
Jeremy HowardYouTube ↗
Further reading 3
Will the leaderboard winner solve your problem? →A public score can shortlist models. A new version of your own task can reveal what the score misses.How far is next-token prediction from answering a person? →Separate three questions: how an input becomes a representation, how training changes a network and how a capable text predictor becomes an assistant. An explanation at one level does not settle the others.This video helps answer · From predicting a token to using a language modelHow much does a successful demonstration establish? →A program gives the expected output. Between “it did” and “it will” lie the test distribution, formal assumptions and deployment context. Those boundaries are easy to miss under pressure to ship.This video helps answer · What if the model has already seen the test?
Caption notes
Howard connects next-token training to practical assistants through code: prompting, function calls, local quantized models and retrieval.
Original passages · 5
these metrics are not particularly well aligned with real life usagethere's no context here being sent to the embedding model so it's actually going to have no idea I'm talking about new lmfitit does not actually return the number nine instead it returns something saying please call a functionknows how to predict the next wordthis is called retrieval augmented generation