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.
PyTorch
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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. -
Delivering reliable production experiences with PyTorch Enterprise on Microsoft Azure
At Microsoft, we use PyTorch to power products such as Bing and Azure Cognitive Services and we actively contribute to several PyTorch open-source projects, including PyTorch Profiler, ONNX Runtime, DeepSpeed, and more. -
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 generative transformer model for code, a. -
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. -
Accelerate PyTorch training with torch-ort
With a simple change to your PyTorch training script, you can now speed up training large language models with torch_ort. -
Introducing Distributed Data Parallel support on PyTorch Windows
Model training has been and will be in the foreseeable future one of the most frustrating things machine learning developers face. -
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. -
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. -
Optimizing and deploying transformer INT8 inference with ONNX Runtime-TensorRT on NVIDIA GPUs
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. -
Olive: A user-friendly toolchain for hardware-aware model optimization
Introducing Olive, an easy-to-use toolchain for optimizing models with hardware awareness. -
Introducing ONNX Script: Authoring ONNX with the ease of Python
ONNX Script is a new open-source library for directly authoring ONNX models in Python.
Microsoft Open Source
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