Why Low-Level Training Frameworks Save Us (Part 2)
Hosted by Zach Mueller
What you'll learn
What's the best medium to learn what's actually happening?
The Trainer helps you get off the ground, but is it the best way to learn by digging through thousands of lines of code?
Low-level frameworks help teach you
Since at most they're a light wrapper of a concept, low level API's make code approachable for learning
Less bumps in the road
Since they are *under abstracted*, low level frameworks help get you started faster in the long-run
Why this topic matters
The Trainer and other high-level wrappers are great for getting you started. But when trying to master deep learning training you shouldn't be relying on these tools forever. It's critical to make sure you know how they work under the hood.
Low level training frameworks help ensure this by keeping abstraction minimal, code readable, and help facilitate a learning path high-level ones can't do
You'll learn from
Zach Mueller
Instructor, Technical Lead at Hugging Face
I've been in the field for almost a decade now. I first started in the fast.ai community, quickly learning how modern-day training pipelines are built and operated. Then I moved to Hugging Face, where I'm the Technical Lead on the accelerate project and manage the transformers Trainer.
I've written numerous blogs, courses, and given talks on distributed training and PyTorch throughout my career.
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