Transformers is Hugging Face's open-source framework for working with state-of-the-art pretrained machine-learning models. It provides standardized model definitions and APIs for text, computer vision, audio, video, and multimodal workloads, supporting both inference and training across a large ecosystem of modern AI models.

A major role of Transformers is to provide a common model layer that can be reused across the AI ecosystem. Models supported by the library can work with numerous training frameworks, inference engines, and adjacent modeling tools. Users can access more than a million model checkpoints through the Hugging Face Hub and load many of them with relatively little code.

For application development, the high-level Pipeline API simplifies common tasks such as text generation, conversational AI, automatic speech recognition, and image classification by handling much of the required preprocessing and output processing. At the same time, developers and researchers can work directly with model and tokenizer classes when they need greater control over training, inference, configuration, or customization.