Video Training / IT and Programming for PC Tutorials →Hugging Face in Action, Video Edition

Everything you need to know about using the tools, libraries, and models at Hugging Face—from transformers, to RAG, LangChain, and Gradio.
Hugging Face in Action reveals how to get the absolute best out of everything Hugging Face, from accessing state-of-the-art models to building intuitive frontends for AI apps.
With Hugging Face in Action you'll learn
Utilizing Hugging Face Transformers and Pipelines for NLP tasks
Applying Hugging Face techniques for Computer Vision projects
Manipulating Hugging Face Datasets for efficient data handling
Training Machine Learning models with AutoTrain functionality
Implementing AI agents for autonomous task execution
Developing LLM-based applications using LangChain and LlamaIndex
Constructing LangChain applications visually with LangFlow
Creating web-based user interfaces using Gradio
Building locally running LLM-based applications with GPT4ALL
Querying local data using Large Language Models
Want a cutting edge transformer library? Hugging Face's open source offering is best in class. Need somewhere to host your models? Hugging Face Spaces has you covered. Do your users need an intuitive frontend for your AI app? Hugging Face's Gradio library makes it easy to build UI using the Python skills you already have. In Hugging Face in Action you'll learn how to take full advantage of all of Hugging Face's amazing features to quickly and reliably prototype and productionize AI applications.
About the Technology
Hugging Face is an incredible open-source ecosystem for AI engineers and data scientists, providing hundreds of pre-trained models, datasets, tools, and libraries. It's also a central hub for collaborating on leading edge AI research. Hugging Face is a massive platform, and this book will help you take full advantage of all it has to offer.
About the Book
Hugging Face in Action teaches you how to build end-to-end AI systems using resources from the Hugging Face community. In it, you'll create multiple projects, including an object detection model, a RAG Q&A application, an LLM-powered chatbot, and more. You'll appreciate the clear, accessible explanations, along with thoughtful introductions to key technologies like LangChain, LlamaIndex, and Gradio.
What's Inside
How to navigate the huge Hugging Face library of models and tools
How to run LLMs locally using GPT4ALL
How to create web-based user interfaces using Gradio
How to improve models using Hugging Face datasets
About the Reader
For Python programmers familiar with NumPy and Pandas. No AI experience required.
About the Author
Wei-Meng Lee is a technologist and founder of Developer Learning Solutions.