使用 Hugging Face Transformers 與 AWS Inferentia 加速 BERT 推論
Original: Accelerate BERT inference with Hugging Face Transformers and AWS Inferentia
When deploying large language models such as BERT in production environments, inference latency and computational cost are often two major…
本教學介紹如何結合 Hugging Face Transformers、AWS Neuron SDK 與 Amazon SageMaker，在 AWS Inferentia (inf1) 實例上部署 BERT 模型。透過將模型編譯為 Neuron 格式，開發者能以極低的延遲和更低的成本進行大規模 NLP 推論，非常適合需要高吞吐量生產環境的團隊。
When deploying large language models such as BERT in production environments, inference latency and computational cost are often two major pain points for enterprises. Traditionally, using GPUs (such as NVIDIA chips) offers fast speeds but comes with prohibitively high hardware costs. The Inferentia chip introduced by AWS (available on `inf1` instances) is purpose-designed for machine learning inference, aiming to deliver exceptional price-to-performance ratios.
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