Hugging Face Transformers

Transformers is Hugging Face's open-source model-definition framework and Python library for inference and training with pretrained text, computer vision, audio, video, and multimodal machine-learning models. It centralizes model definitions behind a unified API and provides the Pipeline interface, which preprocesses inputs and returns task-specific outputs for applications such as text generation, automatic speech recognition, image classification, and visual question answering. Models can be downloaded and cached from the Hugging Face Hub, and the library supports moving models between PyTorch, JAX, and TensorFlow workflows while exposing model internals for customization. It requires Python 3.10 or later and PyTorch 2.5 or later for the documented installation.

Hugging Face is an AI and machine-learning collaboration platform that hosts and distributes models, datasets, and applications. Its Hub supports public model, dataset, and application repositories across text, image, video, audio, and 3D workloads, while its open-source stack includes Transformers, Diffusers, Safetensors, Tokenizers, TRL, Transformers.js, smolagents, and PEFT. The platform provides a unified API for accessing models from AI providers, GPU-based compute and Inference Endpoints, and paid team and enterprise features such as private datasets, access controls, single sign-on, audit logs, and dedicated support.

The Hugging Face LLM Course is a free educational course covering large language models, natural language processing, and the Hugging Face ecosystem. It teaches Transformer concepts and use of Transformers, Datasets, Tokenizers, Accelerate, and the Hugging Face Hub; later chapters cover classic NLP tasks, model demos, fine-tuning, dataset curation, and reasoning models. The course includes code that can be run in Google Colab or Amazon SageMaker Studio Lab, requires good Python knowledge, and recommends prior introductory deep-learning study. It is released under the Apache 2 license, with contributions supported through issues, translations, and the course repository.

A Hugging Face tokenization tool used to convert text into tokens and to detokenize token sequences back into text, including as part of an inference request's processing pipeline.

TensorFlow is an open-source, end-to-end machine-learning platform originally developed by Google Brain. It provides tools, libraries, community resources, and stable Python and C++ APIs for building, training, and deploying machine-learning applications, with support for CPU and GPU execution and additional device plugins. In TensorFlow-based deployment stacks, it provides serving infrastructure and the SavedModel format; JAX graphs can be converted to SavedModel for integration with TensorFlow serving. The project is distributed through PyPI packages, Docker containers, and source builds, including CPU-only and nightly packages.