By an ML Engineer who’s all the time studying, throughout software program, finance, consulting, and advertising and marketing
I’ve worn many hats in my profession — from writing code at a software program startup, to crunching numbers in finance, advising shoppers as a marketing consultant, and even dabbling in advertising and marketing analytics. Via all of it, one factor has been fixed: the necessity to sustain with the breakneck tempo of expertise.
As an ML engineer, you’ve doubtless seen that fine-tuning is popping up in every single place these days. The subject of coaching giant language fashions (LLMs) to do sure jobs or conform to human tastes is now trending. Individuals are speaking about Hugging Face TRL and different libraries as the following massive factor, together with phrases like RLHF and PPO.
Let’s discover, in plain English, what fine-tuning is, how it’s finished, and the way new approaches like Reinforcement Studying from Human Suggestions (RLHF) are altering the sport. I’ll additionally introduce Hugging Face’s TRL library, which has helped me tremendously in making these subtle fine-tuning methods simpler to know. My aim is to supply a concise abstract (with out technical jargon) of why this rising discipline is necessary for engineers to know.
