Optimizing and deploying transformer INT8 inference with ONNX Runtime-TensorRT on NVIDIA GPUs 

5 min read

Mohit Ayani, Solutions Architect, NVIDIA Shang Zhang, Senior AI Developer Technology Engineer, NVIDIA Jay Rodge, Product Marketing Manager-AI, NVIDIA Transformer-based models have revolutionized the natural language processing (NLP) domain. Ever since its inception, transformer architecture has been integrated into models like Bidirectional Encoder Representations from Transformers (BERT) and Generative Pre-trained Transformer (GPT) for performing tasks Read more

Scaling-up PyTorch inference: Serving billions of daily NLP inferences with ONNX Runtime 

8 min read

Scale, performance, and efficient deployment of state-of-the-art Deep Learning models are ubiquitous challenges as applied machine learning grows across the industry. We’re happy to see that the ONNX Runtime Machine Learning model inferencing solution we’ve built and use in high-volume Microsoft products and services also resonates with our open source community, enabling new capabilities that Read more

Supporting efficient large model training on AMD Instinct™ GPUs with DeepSpeed 

6 min read

This post was co-authored by Jithun Nair and Aswin Mathews, members of technical staff at AMD. In recent years, large-scale deep learning models have demonstrated impressive capabilities, excelling at tasks across natural language processing, computer vision, and speech domains. Companies now use these models to power novel AI-driven user experiences across a whole spectrum of Read more

Add AI to mobile applications with Xamarin and ONNX Runtime 

2 min read

ONNX Runtime now supports building mobile applications in C# with Xamarin. Support for Android and iOS is included in the ONNX Runtime release 1.10 NuGet package. This enables C# developers to build AI applications for Android and iOS to execute ONNX models on mobile devices with ONNX Runtime. ONNX Runtime is the open source project Read more

ONNX Runtime Web—running your machine learning model in browser 

5 min read

We are introducing ONNX Runtime Web (ORT Web), a new feature in ONNX Runtime to enable JavaScript developers to run and deploy machine learning models in browsers. It also helps enable new classes of on-device computation. ORT Web will be replacing the soon to be deprecated onnx.js, with improvements such as a more consistent developer Read more

Accelerate PyTorch training with torch-ort 

3 min read

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 

4 min read

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 

7 min read

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 

7 min read

“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