Few-Shot Learning in Production

Explore few-shot learning techniques for production environments in this comprehensive workshop presented by researchers from Hugging Face and Intel AI. Learn to train Sentence Transformers using SetFit, a powerful technique for scenarios with limited labeled data. Discover methods for compressing models through knowledge distillation and accelerating inference using quantization with 🤗 Optimum and Intel® Neural Compressor. Gain insights into deploying models efficiently with Inference Endpoints. Dive into topics such as Fuchsia, TPU, benchmarks, use cases, and various training techniques. Follow along with practical demonstrations using notebooks and explore real-world applications in random news scenarios. By the end of this 1 hour and 22 minute session, acquire valuable skills for implementing few-shot learning in production environments.

Introduction
What is Fuchsia
TPU
Setfit
Summary
Benchmarks
Use cases
Techniques
Knowledge distillation
Quantization
Training Sets
Random News
Notebook
Deployment