philschmid blog

Going Production: Auto-scaling Hugging Face Transformers with Amazon SageMaker

October 29, 20216 min read

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

Deploy BigScience T0_3B to AWS & Amazon SageMaker

October 20, 20215 min read

馃尭 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!

Scalable, Secure Hugging Face Transformer Endpoints with Amazon SageMaker, AWS Lambda, and CDK

October 06, 20216 min read

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

Few-shot learning in practice with GPT-Neo

June 05, 20216 min read

The latest developments in NLP show that you can overcome this limitation by providing a few examples at inference time with a large language model - a technique known as Few-Shot Learning. In this blog post, we'll explain what Few-Shot Learning is, and explore how a large language model called GPT-Neo.

Distributed Training: Train BART/T5 for Summarization using 馃 Transformers and Amazon SageMaker

April 09, 202110 min read

Learn how to train distributed models for summarization using Hugging Face Transformers and Amazon SageMaker and upload them afterwards to

Multilingual Serverless XLM RoBERTa with HuggingFace, AWS Lambda

December 17, 202013 min read

Learn how to build a Multilingual Serverless BERT Question Answering API with a model size of more than 2GB and then testing it in German and France.

Serverless BERT with HuggingFace, AWS Lambda, and Docker

December 06, 202013 min read

Learn how to use the newest cutting edge computing power of AWS with the benefits of serverless architectures to leverage Google's "State-of-the-Art" NLP Model.

AWS Lambda with custom docker images as runtime

December 02, 20208 min read

Learn how to build and deploy an AWS Lambda function with a custom python docker container as runtime with the use of Amazon ECR.