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Improve BERT inference speed by combining the power of Optimum, OpenVINO™, ONNX Runtime, and Azure

opensource.microsoft.com · published 25 January 2023

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https://azure.microsoft.com/products/machine-learning/

azure.microsoft.com

https://onnxruntime.ai/docs/execution-providers/OpenVINO-ExecutionProvider.html

onnxruntime.ai

https://huggingface.co/docs/optimum/v1.2.1/en/onnxruntime/hf.co/models

huggingface.co

https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad

huggingface.co

https://huggingface.co/docs/transformers/main/en/main_classes/trainer

huggingface.co

https://github.com/intel/nlp-training-and-inference-openvino/tree/main/question-answering-bert-qat

github.com

https://github.com/microsoft/onnxruntime-inference-examples/tree/main/python/OpenVINO_EP/azureml

github.com

https://medium.com/openvino-toolkit/enhanced-low-precision-pipeline-to-accelerate-inference-with-openvino-toolkit-deefe0206c24

medium.com

https://medium.com/openvino-toolkit/developer-guide-model-optimization-with-the-openvino-toolkit-d19a201dd3ce

medium.com

https://qa.fastforwardlabs.com/no%20answer/null%20threshold/bert/distilbert/exact%20match/f1/robust%20predictions/2020/06/09/Evaluating_BERT_on_SQuAD.html

qa.fastforwardlabs.com