Hugging Face Transformers

Hugging Face Transformers is a Python library that provides a framework for defining and working with machine learning models across text, computer vision, audio, video and multimodal tasks. Developers use it for both training and inference with pre-trained models. The library acts as a central model definition system that ensures compatibility across different training frameworks, inference engines and related modeling libraries. It was developed by Sylain Gugger and Thomas Wolf and is licensed under the Apache Software License 2.0.

The library centralizes model definitions so they are consistent across the machine learning ecosystem. This approach allows models defined in Transformers to work with various training frameworks and inference engines without requiring separate implementations for each. The project is open source and includes extensive documentation and learning resources for developers working with transformer-based models.