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https://aws.amazon.com/blogs/machine-learning/reduce-inference-time-for-bert-models-using-neural-architecture-search-and-sagemaker-automated-model-tuning

Reduce inference time for BERT models using neural architecture search and SageMaker Automated Model Tuning | Amazon Web Services

In this post, we demonstrate how to use neural architecture search (NAS) based structural pruning to compress a fine-tuned BERT model to improve model performance and reduce inference times. Pre-trained language models (PLMs) are undergoing rapid commercial and enterprise adoption in the areas of productivity tools, customer service, search and recommendations, business process automation, and […]



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Reduce inference time for BERT models using neural architecture search and SageMaker Automated Model Tuning | Amazon Web Services

https://aws.amazon.com/blogs/machine-learning/reduce-inference-time-for-bert-models-using-neural-architecture-search-and-sagemaker-automated-model-tuning

In this post, we demonstrate how to use neural architecture search (NAS) based structural pruning to compress a fine-tuned BERT model to improve model performance and reduce inference times. Pre-trained language models (PLMs) are undergoing rapid commercial and enterprise adoption in the areas of productivity tools, customer service, search and recommendations, business process automation, and […]



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https://aws.amazon.com/blogs/machine-learning/reduce-inference-time-for-bert-models-using-neural-architecture-search-and-sagemaker-automated-model-tuning

Reduce inference time for BERT models using neural architecture search and SageMaker Automated Model Tuning | Amazon Web Services

In this post, we demonstrate how to use neural architecture search (NAS) based structural pruning to compress a fine-tuned BERT model to improve model performance and reduce inference times. Pre-trained language models (PLMs) are undergoing rapid commercial and enterprise adoption in the areas of productivity tools, customer service, search and recommendations, business process automation, and […]

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      In this post, we demonstrate how to use neural architecture search (NAS) based structural pruning to compress a fine-tuned BERT model to improve model performance and reduce inference times. Pre-trained language models (PLMs) are undergoing rapid commercial and enterprise adoption in the areas of productivity tools, customer service, search and recommendations, business process automation, and […]

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