Hyperproductive Machine Learning with Transformers and Hugging Face

In just a couple of years, transformers have emerged as a general-purpose architecture for ML. Not just for Natural Language Processing, but also Speech, Computer Vision or even protein structure prediction. Indeed, the Transformer architecture has proven very efficient on a wide variety of Machine Learning tasks. But how can we keep up with the frantic pace of innovation? Do we really need expert skills to leverage these state-of-the-art models? Or is there a shorter path to creating business value in less time? In this code-level talk, we’ll show you how to quickly build and deploy machine learning applications based on Transformers models. Along the way, you’ll learn about the portfolio of open source and commercial Hugging Face solutions, and how they can help you deliver high-quality machine learning solutions faster than ever before.