Deploy GPT-J 6B for inference with Hugging Face Transformers on Amazon SageMaker

AI Impact Summary

GPT-J 6B can be deployed in production via Hugging Face Transformers on Amazon SageMaker, using a model.tar.gz artifact stored in S3 and the HuggingFaceModel class. The model weighs ~24GB in FP32, with FP16 and low_cpu_mem_usage helping memory, but initial load times were minutes in trials, so production deployments should favor pre-warmed or on-disk artifacts and optimized container images. The setup targets real-time inference within SageMaker's typical 60-second response window, making endpoint sizing and potential batch-transform options essential for longer predictions. This enables an open-source GPT-J deployment path with scalable real-time inference, but demands careful memory planning, artifact management, and cost-aware instance sizing.