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We’ve noticed an unusual training pattern in fine-tuning LLMs. At first we thought it’s a bug, but now we think it shows LLMs can learn effectively from a single example. Summary: recently while fine-tuning a large language model (LLM) on multiple-choice science exam questions, we observed some highly unusual training loss curves. In particular, it appeared the model was able to rapidly memorize e
I remember the first time I used the v1.0 of Visual Basic. Back then, it was a program for DOS. Before it, writing programs was extremely complex and I’d never managed to make much progress beyond the most basic toy applications. But with VB, I drew a button on the screen, typed in a single line of code that I wanted to run when that button was clicked, and I had a complete application I could now
Practical Deep Learning for Coders 2019 Written: 24 Jan 2019 by Jeremy Howard Launching today, the 2019 edition of Practical Deep Learning for Coders, the third iteration of the course, is 100% new material, including applications that have never been covered by an introductory deep learning course before (with some techniques that haven’t even been published in academic papers yet). There are sev
Launching Cutting Edge Deep Learning for Coders: 2018 edition Written: 07 May 2018 by Jeremy Howard About the course Today we are launching the 2018 edition of Cutting Edge Deep Learning for Coders, part 2 of fast.ai’s free deep learning course. Just as with our part 1 Practical Deep Learning for Coders, there are no pre-requisites beyond high school math and 1 year of coding experience—we teach y
Courses: Practical Deep Learning for Coders; From Deep Learning Foundations to Stable Diffusion Software: fastai for PyTorch; nbdev Book: Practical Deep Learning for Coders with fastai and PyTorch In the news: The Economist; The New York Times; MIT Tech Review Corporate partner program: Get help with fast.ai technologies & courses from the partner program Blog
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