ONNX Runtime Web unleashes generative AI in the browser using WebGPU
ONNX Runtime Web featuring WebGPU is now available in the ONNX Runtime 1.
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Olive: A user-friendly toolchain for hardware-aware model optimization
Introducing Olive, an easy-to-use toolchain for optimizing models with hardware awareness. -
Automate optimization techniques for transformer models
Intel has collaborated with Microsoft to integrate Intel® Neural Compressor into Olive, enabling developers to easily take advantage of model compression techniques in their deployment platform, including Intel processors and accelerators. -
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. -
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 to run and deploy machine learning models in browsers. -
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. -
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).
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