Learn how to optimize BERT for GPU inference with a 1-line of code using Hugging Face Transformers and DeepSpeed.

Learn how to optimize Sentence Transformers using Hugging Face Optimum. You will learn how dynamically quantize and optimize a Sentence Transformer for ONNX Runtime.

Learn how to migrate your training jobs to a Habana Gaudi-based DL1 instance on AWS using EC2 Remote Runner.

Learn how to optimize Vision Transformer (ViT) using Hugging Face Optimum. You will learn how dynamically quantize a ViT model for ONNX Runtime.

Learn how to optimize Hugging Face Transformers models for NVIDIA GPUs using Optimum. You will learn how to optimize a DistilBERT for ONNX Runtime

Learn how to learn how to fine-tune XLM-RoBERTa for multi-lingual multi-class text-classification using a Habana Gaudi-based DL1 instance.

Learn how to optimize Hugging Face Transformers models using Optimum. The session will show you how to dynamically quantize and optimize a DistilBERT model using Hugging Face Optimum and ONNX Runtime. Hugging Face Optimum is an extension of 🤗 Transformers, providing a set of performance optimization tools enabling maximum efficiency to train and run models on targeted hardware.

Introduction guide about ONNX and Transformers. Learn how to convert transformers like BERT to ONNX and what you can do with it.

Learn how to setup a Deep Learning Environment for Hugging Face Transformers with Habana Gaudi on AWS using the DL1 instance type.

Learn how to do post-training static quantization on Hugging Face Transformers model with `optimum` to achieve up to 3x latency improvements.