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…
Topic: AI + Machine Learning
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…
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…
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…
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…
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…