(NLP) Achieve ML Hyper-productivity with Hugging Face Transformers
Time and Location
Sep-9, 2022 at 9:00am - 3:00pm EDT
The Westin Atlanta Perimeter North
In this workshop, you'll walk through a complete end-to-end example of using Hugging Face Transformers, involving both our open-source libraries and some of our commercial products.
Starting from a dataset containing real-life product reviews from Amazon.com, you'll train and deploy a text classification model predicting the star rating for similar reviews.
Along the way, you'll learn how to:
- Explore models and datasets on the Hugging Face Hub,
- Load, prepare and save datasets with the Hugging Face datasets library,
- Load, train and save models with the Hugging Face transformers library,
- Build ML applications with Hugging Spaces to showcase your models,
- Use hardware acceleration with the Hugging Face Optimum library to optimize training and prediction times,
- and maybe a few more things, if we have time!
Of course, all code will be shared with you, and you'll be able to use it easily in your own projects.
This is a hands-on, code-level workshop all the way. Coding proficiency is required
Participants don't need to be ML experts, but they must be familiar with basic ML concepts and workflows, as well as Python and Python-based tools for ML (Jupyter, numpy, pandas, etc.).
Participants must bring their own laptop.
Prior to the workshop, participants must set up a cloud-based Jupyter environment with GPU support (Google Colab, Amazon SageMaker Studio Lab or Amazon SageMaker Studio) and Git LFS support (https://git-lfs.github.com).
No time will be allocated for setupup during the workshop.
Google Colab Paid Version $10 (https://colab.research.google.com/signup)