Building Blocks for Foundation Model Training and Inference on AWS
This Hugging Face blog post, published in partnership with Amazon, outlines the infrastructure components available on AWS for training and serving foundation models. It covers the key building blocks including compute, storage, networking, and managed services relevant to large-scale AI workloads. The post serves as a technical overview of AWS's positioning in the foundation model infrastructure space.
Related guides (4)
Related events (8)
Hugging Face and AWS Partner to Make AI More Accessible
Hugging Face announced a strategic partnership with Amazon Web Services to expand access to AI models and tools. The collaboration aims to integrate Hugging Face's model hub and libraries more deeply with AWS infrastructure and services. This represents a significant enterprise deployment and cloud distribution move for the open-source AI ecosystem.
Deploy models on AWS Inferentia2 from Hugging Face
Hugging Face has announced support for deploying models on AWS Inferentia2 via Hugging Face Inference Endpoints. The integration allows users to deploy popular open-weight models on AWS's custom ML accelerator chips directly from the Hugging Face Hub. This expands the hardware options available for cost-effective inference beyond standard GPU instances.
Deploy Hugging Face Models Easily with Amazon SageMaker
Hugging Face and Amazon SageMaker announced an integration enabling streamlined deployment of Hugging Face models via SageMaker's managed infrastructure. The partnership provides dedicated Hugging Face Deep Learning Containers on AWS, simplifying the path from model hub to production inference. This represents an early milestone in the enterprise deployment pattern of hosted model hubs integrating with cloud ML platforms.
Accelerating Hugging Face Transformers with AWS Inferentia2
Hugging Face published a blog post detailing how to accelerate Transformer model inference using AWS Inferentia2, Amazon's second-generation ML inference chip. The post covers integration patterns between the Hugging Face ecosystem and the Neuron SDK for deploying models on Inferentia2 hardware. This represents a practical guide for enterprise and cloud-based inference deployment using dedicated AI accelerators.
How to Deploy and Fine-Tune DeepSeek Models on AWS
Hugging Face published a guide covering deployment and fine-tuning of DeepSeek models on AWS infrastructure. The post addresses practical integration patterns for running DeepSeek-R1 and related models using AWS services alongside Hugging Face tooling. This is a tier-2 commentary/tutorial piece targeting practitioners who want to operationalize DeepSeek models in cloud environments.
Accelerate BERT inference with Hugging Face Transformers and AWS Inferentia
This Hugging Face blog post describes how to deploy BERT models on AWS Inferentia chips using the Hugging Face Transformers library and Amazon SageMaker. It covers the workflow for compiling models with AWS Neuron SDK and running optimized inference on Inferentia hardware. The post targets practitioners looking to reduce inference costs and latency for transformer-based NLP workloads.
Anthropic and AWS expand partnership with $4B investment and Trainium hardware collaboration
Anthropic announced an expanded partnership with Amazon Web Services, including a new $4 billion investment that brings Amazon's total stake to $8 billion, while establishing AWS as Anthropic's primary cloud and training partner. The collaboration includes deep hardware-software co-development on AWS Trainium accelerators, with Anthropic engineers writing low-level kernels and contributing to the AWS Neuron software stack to optimize model training from the silicon up. Claude on Amazon Bedrock is described as core infrastructure for tens of thousands of enterprises, with named deployments at Pfizer, Intuit, Perplexity, and the European Parliament. The deal also extends Claude's availability to AWS GovCloud and classified cloud regions for government customers.
The Partnership: Amazon SageMaker and Hugging Face
Hugging Face and Amazon announced a partnership integrating Hugging Face models and tools natively into Amazon SageMaker. This collaboration enables developers to train and deploy Hugging Face Transformers models directly within SageMaker's managed ML infrastructure. The partnership represents an early major cloud-provider integration for Hugging Face, expanding enterprise access to open-source NLP models.