Deep Learning Library / Machine Learning Framework
159.3k 2026-04-13
huggingface/transformers
A unified framework providing state-of-the-art machine learning models for text, vision, audio, and multimodal tasks, optimized for both inference and training.
Core Features
Offers a vast collection of pre-trained state-of-the-art models.
Supports diverse modalities including text, vision, audio, and multimodal data.
Provides a centralized model definition compatible with major deep learning frameworks.
Optimized for both efficient model inference and robust training workflows.
Detailed Introduction
Hugging Face Transformers is a pivotal open-source library that centralizes the definition and implementation of state-of-the-art machine learning models. It serves as a comprehensive framework for developers and researchers working with various data types, including text, computer vision, audio, and multimodal inputs. By offering a unified interface, Transformers ensures model compatibility across a wide array of training frameworks and inference engines, streamlining the development and deployment of advanced AI applications.