3 new videos: Intel Sapphire Rapids inference, few-shot learning with SetFit, and semantic search on images and videos with BridgeTower

Not one, but three new Hugging Face videos today :) Learn and share!

In this video, you will learn how to accelerate PyTorch inference with an Intel Sapphire Rapids server running on AWS. Working with popular Hugging Face transformers implemented with PyTorch, we’ll first measure their performance on an Ice Lake server for short and long NLP token sequences. Then, we’ll do the same with a Sapphire Rapids server and the latest version of Hugging Face Optimum Intel, an open-source library dedicated to hardware acceleration for Intel platforms.

In this video, I’m using SetFit, an open source library for few-shot learning to train a text classification model from only 16 labeled samples. In less than 2.5 minutes of CPU training, I get an accuracy of 94.5% :)

BridgeTower is a new vision-language multimodal model by Intel and Microsoft. In this video, I show you two quick demos for semantic search on images and videos.