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Accelerate PyTorch training with torch-ort 

With a simple change to your PyTorch training script, you can now speed up training large language models with torch_ort.ORTModule, running on the target hardware of your choice. Training deep learning models requires ever-increasing compute and memory resources. Today we release torch_ort.ORTModule, to accelerate distributed training of PyTorch models, reducing the time and resources needed...Read more

ONNX Runtime release 1.8.1 previews support for accelerated training on AMD GPUs with the AMD ROCm™ Open Software Platform 

This post was co-authored by Jeff Daily, a Principal Member of Technical Staff, Deep Learning Software for AMD. ONNX Runtime is an open-source project that is designed to accelerate machine learning across a wide range of frameworks, operating systems, and hardware platforms. Today, we are excited to announce a preview version of ONNX Runtime in...Read more

Simple steps to create scalable processes to deploy ML models as microservices 

This post was co-authored by Alejandro Saucedo, Director of Machine Learning Engineering at Seldon Technologies. About the co-author: Alejandro leads teams of machine learning engineers focused on the scalability and extensibility of machine learning deployment and monitoring products with over five million installations. Alejandro is also the Chief Scientist at the Institute for Ethical AI...Read more

Journey to optimize large scale transformer model inference with ONNX Runtime 

“With its resource-efficient and high-performance nature, ONNX Runtime helped us meet the need of deploying a large-scale multi-layer generative transformer model for code, a.k.a., GPT-C, to empower IntelliCode with the whole line of code completion suggestions in Visual Studio and Visual Studio Code.” Large-scale transformer models, such as GPT-2 and GPT-3, are among the most...Read more