How to Use Hugging Face Transformer Models in MATLAB

Learn how to use Hugging Face transformer models for natural language processing (NLP) tasks in MATLAB®.

Transformer models have been shown to achieve superior results in many NLP tasks. You can use transformer models such as BERT and GPT-2 in MATLAB for text-based applications with Text Analytics Toolbox™ and Deep Learning Toolbox™. You can also use models from external frameworks, such as Hugging Face transformers with text data in MATLAB. 

We walk through the steps of using a Hugging Face transformer model to perform machine translation and analyze the text data using Text Analytics Toolbox, creating a complete NLP pipeline.

Additional resources: 

- Language Translation Using Deep Learning: https://bit.ly/3lrr5Mx

- Mapping Python types with MATLAB types: https://bit.ly/37TT1pk

- How to use BERT for classifying factory reports: https://bit.ly/3woA8Es

Related Products: 

- Text Analytics Toolbox: https://bit.ly/3P4xrij

- Deep Learning Toolbox: https://bit.ly/3P3XRAT