Accelerating over 130,000 Hugging Face models with ONNX Runtime

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What is ONNX Runtime?

ONNX Runtime is a cross-platform machine learning tool that can be used to accelerate a wide variety of models, particularly those with ONNX support.

Hugging Face ONNX Runtime Support

There are over 130,000 ONNX-supported models on Hugging Face, an open source community that allows users to build, train, and deploy hundreds of thousands of publicly available machine learning models. These ONNX-supported models, which include many increasingly popular large language models (LLMs) and cloud models, can leverage ONNX Runtime to improve performance, along with other benefits. For example, using ONNX Runtime to accelerate the whisper-tiny model can improve average latency per inference, with an up to 74.30% gain over PyTorch. ONNX Runtime works closely with Hugging Face to ensure that the most popular models on the site are supported. In total, over 90 Hugging Face model architectures are supported by ONNX Runtime, including the 11 most popular architectures (where popularity is determined by the corresponding number of models uploaded to the Hugging Face Hub):

Model Architecture

Approximate No. of Models

BERT

28180

GPT2

14060

DistilBERT

11540

RoBERTa

10800

T5

10450

Wav2Vec2

6560

Stable-Diffusion

5880

XLM-RoBERTa

5100

Whisper

4400

BART

3590

Marian

2840

Learn More

To learn more about accelerating Hugging Face models with ONNX Runtime, check out our recent post on the Microsoft Open Source Blog.