Supporting efficient large model training on AMD Instinct™ GPUs with DeepSpeed
This post was co-authored by Jithun Nair and Aswin Mathews, members of technical staff at AMD. In recent…
Tag: ONNX Runtime
Add AI to mobile applications with Xamarin and ONNX Runtime
ONNX Runtime now supports building mobile applications in C# with Xamarin. Support for Android and iOS is included…
ONNX Runtime Web—running your machine learning model in browser
We are introducing ONNX Runtime Web (ORT Web), a new feature in ONNX Runtime to enable JavaScript developers…
Accelerate PyTorch training with torch-ort
With a simple change to your PyTorch training script, you can now speed up training large language models…
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.…
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:…
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…
ONNX Runtime 1.8: mobile, web, and accelerated training
The V1.8 release of ONNX Runtime includes many exciting new features. This release launches ONNX Runtime machine learning…
Introducing ONNX Runtime mobile – a reduced size, high performance package for edge devices
ONNX Runtime is an open source project that is designed to accelerate machine learning across a wide range of…
GPT-2 fine-tuning with ONNX Runtime – a 34% speedup in training time
Model training is an important step when developing and deploying large scale Artificial Intelligence (AI) models. Training typically…