AI BriefingHugging Face Supports Inference Acceleration for Optimum
Key point
Hugging Face has updated the features of the Optimum library, which optimizes inference performance for Transformers models.
Details
Hugging Face's open-source library Optimum has added inference support for Transformers pipelines. This allows users to leverage accelerated runtimes such as ONNX Runtime to maximize model efficiency, in a manner compatible with the existing Transformers API.
The key features and characteristics are as follows:
- API Compatibility: Optimized models can be used simply by replacing
AutoModelForXxxwithORTModelForXxx - Hugging Face Hub Integration: Optimized checkpoints can be imported directly from or uploaded to the Hub
- Optimization Tools Provided: Support for model quantization and graph optimization via ORTQuantizer and ORTOptimizer
This update provides developers looking to deploy Transformer-based models like BERT into large-scale production environments with tools to improve model serving speed and efficiency.
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