Connect fluid dynamics, machine learning, and virtual reality with ONNX Runtime
Using ONNX Runtime to unlock the promise of developments in science for solving real world problems.
Topic: AI + Machine Learning
On-Device Training with ONNX Runtime: A deep dive
Building upon the foundation we established earlier, this blog will present comprehensive information about the underlying details of training models directly on user devices using ORT. Equipped with these technical details, we encourage you to try out On-Device Training with ONNX Runtime for your custom scenario.
On-Device Training: Efficient training on the edge with ONNX Runtime
ONNX Runtime is a high-performance cross-platform inference and training engine that can run a variety of machine learning models. ORT provides an easy-to-use experience for the AI developers to run models on multiple hardware and software platforms.
Join Microsoft at KubeCon and CloudNativeCon Europe 2023
As we come together in Amsterdam, there are significant headwinds and challenges facing us, but I’m confident that open-source and cloud-native computing are critical parts of the solutions.
Announcing the availability of Feathr 1.0
Today, we are excited to announce the much-anticipated availability of the OSS Feathr 1.0.
Performant on-device inferencing with ONNX Runtime
The team at Pieces shares the problems and solutions evaluated for their on-device model serving stack and how ONNX Runtime enables their success.
Improve BERT inference speed by combining the power of Optimum, OpenVINO™, ONNX Runtime, and Azure
Make large models smaller and faster with OpenVino Execution Provider, NNCF and ONNX Runtime leveraging Azure Machine Learning.
Feathr feature store joins LF AI & Data Foundation
Together with our colleagues at LinkedIn, we are happy to announce that Feathr is joining the LF AI Data Foundation, an umbrella foundation of the Linux Foundation supporting open source innovation in AI and data.
Live demos of machine learning models with ONNX and Hugging Face Spaces
Choosing which machine learning model to use, sharing a model with a colleague, and quickly trying out a model are all reasons why you may find yourself wanting to quickly run inference on a model.
Scaling-up PyTorch inference: Serving billions of daily NLP inferences with ONNX Runtime
Scale, performance, and efficient deployment of state-of-the-art Deep Learning models are ubiquitous challenges as applied machine learning grows across the industry.
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 years, large-scale deep learning models have demonstrated impressive capabilities, excelling at tasks across natural language processing, computer vision, and speech domains.
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 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.