Sagemaker

Learn how to do advanced PII detection and anonymization with Hugging Face Transformers and Amazon SageMaker.

Learn about the different existing Amazon SageMaker Inference options and and how to use them.

Learn how to do image segmentation with Hugging Face Transformers, SegFormer and Amazon SageMaker.

Learn how to do automatic speech recognition/speech-to-text with Hugging Face Transformers, Wav2vec2 and Amazon SageMaker.

Learn how to leverage AWS Spot Instances when training Hugging Face Transformers with Amazon SageMaker to save up to 90% training cost.

Learn how to use a custom Inference script for creating document embeddings with Hugging Face's Transformers, Amazon SageMaker, and Sentence Transformers.

Learn how to deploy multiple Hugging Face Transformers for inference with Amazon SageMaker and Multi-Container Endpoints.

Learn how to deploy an Asynchronous Inference model with Hugging Face Transformers and Amazon SageMaker, with autoscaling to zero.

Learn how to fine-tune a a Hugging Face Transformer for Financial Text Summarization using vanilla `Keras`, `Tensorflow` , `Transformers`, `Datasets` & Amazon SageMaker.

Learn how to deploy EleutherAIs GPT-J 6B for inference using Hugging Face Transformers and Amazon SageMaker.

In October and November, we held a workshop series on “Enterprise-Scale NLP with Hugging Face & Amazon SageMaker”. This workshop series consisted out of 3 parts and covers: Getting Started, Going Production & MLOps.

Learn how to deploy Hugging Face Transformers serverless using the new Amazon SageMaker Serverless Inference.

Learn how to Compile and fine-tune a Multi-Class Classification Transformers with `Trainer` and `emotion` dataset using Amazon SageMaker Training Compiler.

Learn how to automatically save your model weights, logs, and artifacts to the Hugging Face Hub using Amazon SageMaker and how to deploy the model afterwards for inference.

Learn how to build an End-to-End MLOps Pipeline for Hugging Face Transformers from training to production using Amazon SageMaker.

Learn how to add auto-scaling to your Hugging Face Transformers SageMaker Endpoints.

🌸 BigScience released their first modeling paper introducing T0 which outperforms GPT-3 on many zero-shot tasks while being 16x smaller! Deploy BigScience the 3 Billion version (T0_3B) to Amazon SageMaker with a few lines of code to run a scalable production workload!

Deploy Hugging Face Transformers to Amazon SageMaker and create an API for the Endpoint using AWS Lambda, API Gateway and AWS CDK.