AI BriefingAccelerating BERT Inference with AWS Inferentia
Key point
A guide to optimizing BERT model inference performance and reducing costs using AWS Inferentia and Hugging Face Transformers.
Details
Transformer-based models offer excellent performance, but high cost and complexity during inference remain a challenge. AWS Inferentia is a custom ML chip designed to address this, offering up to 80% lower inference costs and 2.3x higher throughput compared to conventional GPU instances.
Each Inferentia chip includes 4 Neuron Cores, allowing you to load a model onto each core individually to maximize throughput, or utilize all cores to minimize latency.
This guide covers the entire process of converting a Hugging Face Transformers model via the AWS Neuron SDK, and building and evaluating a real-time inference endpoint using Amazon SageMaker.
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