AWS Inferentia2
aws-inferentia2-95037b83·6 events·first seen 28d agoAliases: AWS Inferentia2, AWS Inferentia
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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.
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.
Hugging Face Text Generation Inference available for AWS Inferentia2
Hugging Face has announced that its Text Generation Inference (TGI) serving framework is now available for AWS Inferentia2 accelerators. This integration allows users to deploy large language models on AWS's custom AI chips using the TGI stack. The move extends TGI's hardware support beyond GPUs to specialized inference silicon, potentially offering cost and performance advantages for production LLM deployments.
Make your llama generation time fly with AWS Inferentia2
This Hugging Face blog post covers deploying and optimizing Llama 2 inference on AWS Inferentia2 accelerators. It demonstrates integration between Hugging Face's Optimum Neuron library and AWS's custom silicon to achieve competitive inference throughput and latency. The post serves as a practical guide for enterprise teams looking to reduce inference costs by moving off GPU-based infrastructure.
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.
Amazon invests up to $4 billion in Anthropic, becomes primary cloud provider
Anthropic announced a strategic investment of up to $4 billion from Amazon, with AWS becoming Anthropic's primary cloud provider for mission-critical workloads. The deal includes access to AWS Trainium and Inferentia chips for model training and deployment, expanded Claude availability on Amazon Bedrock with enterprise fine-tuning capabilities, and joint collaboration on future Trainium and Inferentia chip development. Amazon takes a minority stake while Anthropic's governance structure, including its Long Term Benefit Trust, remains unchanged.