---
title: "Securely deploy LLMs inside VPCs with Hugging Face and Amazon SageMaker"
url: https://daily.dev/posts/securely-deploy-llms-inside-vpcs-with-hugging-face-and-amazon-sagemaker-nnj5pxrn5
source_url: https://www.philschmid.de/sagemaker-llm-vpc
type: article
source: "Philipp Schmid"
published: 2026-05-31T07:41:08.404Z
updated: 2026-05-31T08:31:02.093Z
tags: ["python", "aws", "llm"]
reading_time: 5
upvotes: 0
comments: 0
language: en
---

> ## Documentation Index
> Fetch the complete documentation index at: https://daily.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Securely deploy LLMs inside VPCs with Hugging Face and Amazon SageMaker

**[Philipp Schmid](https://daily.dev/sources/philschmid)** · 5 min read · 0 upvotes · 0 comments

## Summary

A step-by-step guide for deploying open-source LLMs to Amazon SageMaker inside a VPC without internet access, using the Hugging Face LLM Inference DLC and loading model weights from Amazon S3. The tutorial covers packaging model weights as a model.tar.gz archive with safetensors format, uploading to S3, retrieving the Hugging Face LLM container image URI, deploying the starchat-beta model on a g5.12xlarge GPU instance with TGI auto-sharding, and running inference — enabling organizations with strict security requirements to serve LLMs in an air-gapped, internet-free environment.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.philschmid.de/sagemaker-llm-vpc>

---

Tags: [#python](https://daily.dev/tags/python), [#aws](https://daily.dev/tags/aws), [#llm](https://daily.dev/tags/llm)

[View this post on daily.dev](https://daily.dev/posts/securely-deploy-llms-inside-vpcs-with-hugging-face-and-amazon-sagemaker-nnj5pxrn5)