Hugging Face Transformers

Transformers from Hugging Face is the model-definition framework behind much of modern machine learning, providing a unified API over more than one million pretrained checkpoints on the Hugging Face Hub. It covers text generation, classification, translation, and summarization, computer vision tasks like detection and segmentation, audio tasks including speech recognition and text-to-speech, and multimodal work such as visual question answering and document understanding. The library acts as a pivot between frameworks, letting a single model definition move across PyTorch, JAX, and TensorFlow and feed downstream training and inference engines. A pipeline API handles common tasks in a few lines, while lower-level classes expose tokenizers, configurations, and model internals for research. Requiring Python 3.10 or newer and released under the Apache 2.0 license, it is the de facto standard interface for transformer models among researchers, engineers, and hobbyists alike.