Microsoft Open Source Blog 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. Read more
ONNX
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. You can configure your environment and download Jupyter notebooks, but it would be nicer if there was a way to Read more
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. 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
Accelerate and simplify Scikit-learn model inference with ONNX Runtime
Scikit-learn is one of the most useful libraries for general machine learning in Python. To minimize the cost of deployment and avoid discrepancies, deploying scikit-learn models to production usually leverages Docker containers and pickle, the object serialization module of the Python standard library. Docker is a good way to create consistent environments and pickle saves Read more
ONNX Runtime scenario highlight: Vespa.ai integration
Since its open source debut two years ago, ONNX Runtime has seen strong growth with performance improvements, expanded platform and device compatibility, hardware accelerator support, an extension to training acceleration, and more. We are excited by its broad usage in production, powering more than a hundred models across Microsoft products and services and bringing concrete Read more
Adding RoBERTa NLP to the ONNX model zoo for natural language predictions
In summer 2019, I worked as a high school intern for the ONNX AI team at Microsoft and loved working on various projects with the team, including the BERT text classification model. However, due to Covid-19, the Microsoft Internship Program for high school students was canceled in the summer of 2020. This led two other Read more
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 frameworks, operating systems, and hardware platforms. Today, we are excited to announce ONNX Runtime release v1.5 as part of our AI at Scale initiative. This release includes ONNX Runtime mobile, a new feature targeting smartphones and other Read more
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 utilizes a large amount of compute resources to tune the model based on the input dataset. Transformer models, with millions and billions of parameters, are especially compute-intensive and training costs increase with model size and fine-tuning steps Read more
Announcing accelerated training with ONNX Runtime—train models up to 45% faster
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. It is used extensively in Microsoft products, like Office 365 and Bing, delivering over 20 billion inferences every day and up to 17 times faster inferencing. Today we are introducing Read more
Microsoft open sources breakthrough optimizations for transformer inference on GPU and CPU
This post is co-authored by Emma Ning, Azure Machine Learning; Nathan Yan, Azure Machine Learning; Jeffrey Zhu, Bing; Jason Li, Bing One of the most popular deep learning models used for natural language processing is BERT (Bidirectional Encoder Representations from Transformers). Due to the significant computation required, inferencing BERT at high scale can be extremely Read more
ONNX joins Linux Foundation
Today the Open Neural Network eXchange (ONNX) is joining the LF AI Foundation, an umbrella foundation of the Linux Foundation supporting open source innovation in artificial intelligence, machine learning, and deep learning. ONNX was co-founded by Microsoft in 2017 to make it easier to create and deploy machine learning applications. In the past few years, Read more
Announcing ONNX Runtime 1.0
One year after ONNX Runtime’s initial preview release, we’re excited to announce v1.0 of the high-performance machine learning model inferencing engine. This release marks our commitment to API stability for the cross-platform, multi-language APIs, and introduces a breadth of performance optimizations, broad operator coverage, and pluggable accelerators to take advantage of new and exciting hardware Read more