1 Introduction to Hugging Face
This chapter covers
- What Hugging Face is known for
- The Hugging Face Transformers library
- Exploring the various models hosted by Hugging Face
- The Gradio library
Hugging Face is an AI community that promotes the building, training, and deployment of open-source machine learning models. It has state-of-the-art models designed for different problem domains, such as: Natural Language Processing (NLP) tasks, Computer vision tasks, and Audio tasks. Besides providing tools for machine learning, Hugging Face also provides a platform for hosting pre-trained models and datasets. With AI at its peak now, Hugging Face is right at the epicenter of the whole AI revolution:
- It unleashes a new wave of applications that capitalize on the large amount of data available.
- A lot of complementary technologies are being developed, such as prototyping tools for LLM-based applications.
- Instead of focusing on the fundamentals (such as building neural networks from scratch or learning machine learning algorithms), developers can now focus on building AI-based apps to solve their problems immediately. AI is now a tool that developers can use directly, and not something that developers have to build themselves from scratch.
- Hugging Face’s philosophy is to promote open-source contributions and it is the hub of open-source models for NLP, computer vision, and other fields where AI plays vital roles.