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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

How to deploy Elastic Cloud on Microsoft Azure 

From startups to the global 2000, Elastic powers search solutions for thousands of companies worldwide to find documents, monitor infrastructure, protect against security threats, and more. With Elastic Cloud managed services on Azure, you have the power of Elastic Enterprise Search, Elastic Observability, and Elastic Security. You can quickly and easily deploy as a managed...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

Accelerate traditional machine learning models on GPU with ONNX Runtime 

With the growing trend towards deep learning techniques in AI, there are many investments in accelerating neural network models using GPUs and other specialized hardware. However, many models used in production are still based on traditional machine learning libraries or sometimes a combination of traditional machine learning (ML) and DNNs. We’ve previously shared the performance...Read more

Open-sourcing TensorFlow with DirectML 

Following the release of our Developer Preview in June, today we’re announcing an exciting next step as we make the source code of TensorFlow-DirectML, an extension of TensorFlow on Windows, available to the public as an open-source project on GitHub. TensorFlow-DirectML broadens the reach of TensorFlow beyond its traditional Graphics Processing Unit (GPU) support, by...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

Hyperspace, an indexing subsystem for Apache Spark™, is now open source 

For Microsoft’s internal teams and external customers, we store datasets that span from a few GBs to 100s of PBs in our data lake. The scope of analytics on these datasets ranges from traditional batch-style queries (e.g., OLAP) to explorative ”finding the needle in a haystack” type of queries (e.g., point-lookups, summarization). Resorting to linear...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

Announcing Applied Cloud Stories 

We are delighted to announce the Applied Cloud Stories initiative by Microsoft! What is Applied Cloud Stories? Do you work with open source? Are you passionate about machine learning or data science? Do you have stories to share about solving scale or data challenges? Are you investing time and effort so that you and your...Read more