Transformers-Tutorials

The Transformers-Tutorials repository provides practical demonstrations of the HuggingFace Transformers library, addressing the need for accessible examples in machine learning and artificial intelligence projects. This resource is particularly beneficial for ML/AI teams, including data scientists and machine learning engineers, who require a solid understanding of transformer models like BERT and GPT-2. While the tutorials are well-structured and informative, they are not a fully-fledged production-ready solution; rather, they serve as educational material for prototyping and experimentation. Teams should avoid relying solely on this repository for mission-critical applications without further development and testing.

This repository is a strong choice for teams looking to quickly understand and implement transformer models in their projects. However, if you require a production-ready solution with extensive support and scalability, consider exploring more mature frameworks or libraries.

Roles such as machine learning engineers, data scientists, and AI researchers will find this repository useful for learning and prototyping. It is typically included in products and systems focused on natural language processing, computer vision, and other AI-driven applications.

Latest commit: 2026-01-13. Over the past 96 days, this repository gained 158 stars (+1.4% growth). Activity data is based on daily RepoPi snapshots of the GitHub repository.