Deploy GPT-J 6B for inference using Hugging Face Transformers and Amazon SageMaker

Hugging Face's SageMaker integration lets you deploy GPT-J 6B as a dedicated endpoint using HuggingFaceModel in under 20 lines of Python. No custom Docker images, no manual model loading. The model runs on ml.g5.2xlarge at roughly $1.50/hr.

For RAG retrieval scoring or document classification at scale, this changes the math. GPT-4o costs ~$0.005 per 1K tokens; a dedicated SageMaker endpoint amortizes to fractions of that at volume. Most teams default to managed APIs even when their workload is predictable enough to justify dedicated inference — that's just laziness with a budget attached.