A step-by-step guide to deploying EleutherAI's GPT-J 6B language model for production inference on Amazon SageMaker using Hugging Face Transformers. The key challenge addressed is model load time: the default loading approach takes over 3 minutes, which exceeds SageMaker's 60-second request limit. The solution uses torch.save/torch.load instead of the standard from_pretrained method, reducing load time from ~83 seconds (with model on disk) down to ~7.7 seconds — a ~10.5x improvement. The tutorial covers saving the model in the torch format, packaging it as a model.tar.gz artifact for S3, deploying a SageMaker real-time endpoint using the HuggingFaceModel class, and running predictions with various decoding strategies including greedy search, beam search, and few-shot prompting.
