{"product_id":"hugging-face-in-action","title":"Hugging Face in Action","description":"\u003cp\u003e\u003cb\u003eEverything you need to know about using the tools, libraries, and models at Hugging Face—from transformers, to RAG, LangChain, and Gradio.\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eHugging Face in Action\u003c\/i\u003e 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.\u003c\/p\u003e\u003cp\u003eWith \u003ci\u003eHugging Face in Action\u003c\/i\u003e you’ll learn:\u003c\/p\u003e\u003cp\u003e• Utilizing Hugging Face Transformers and Pipelines for NLP tasks\u003cbr\u003e• Applying Hugging Face techniques for Computer Vision projects\u003cbr\u003e• Manipulating Hugging Face Datasets for efficient data handling\u003cbr\u003e• Training Machine Learning models with AutoTrain functionality\u003cbr\u003e• Implementing AI agents for autonomous task execution\u003cbr\u003e• Developing LLM-based applications using LangChain and LlamaIndex\u003cbr\u003e• Constructing LangChain applications visually with LangFlow\u003cbr\u003e• Creating web-based user interfaces using Gradio\u003cbr\u003e• Building locally running LLM-based applications with GPT4ALL\u003cbr\u003e• Querying local data using Large Language Models\u003c\/p\u003e\u003cp\u003eWant 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 \u003ci\u003eHugging Face in Action\u003c\/i\u003e 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.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eAbout the technology\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eHugging 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.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eAbout the book\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eHugging Face in Action\u003c\/i\u003e 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\u0026amp;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.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eAbout the author\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eWei-Meng Lee\u003c\/b\u003e is a technologist and founder of Developer Learning Solutions.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e1 Introducing Hugging Face\u003cbr\u003e2 Getting started\u003cbr\u003e3 Using Hugging Face transformers and pipelines for NLP tasks\u003cbr\u003e4 Using Hugging Face for computer vision tasks\u003cbr\u003e5 Exploring, tokenizing, and visualizing Hugging Face datasets\u003cbr\u003e6 Fine-tuning pretrained models and working with multimodal models\u003cbr\u003e7 Creating LLM-based applications using LangChain and LlamaIndex\u003cbr\u003e8 Building LangChain applications visually using Langflow\u003cbr\u003e9 Programming agents\u003cbr\u003e10 Building a web-based UI using Gradio\u003cbr\u003e11 Building locally running LLM-based applications using GPT4All\u003cbr\u003e12 Using LLMs to query your local data\u003cbr\u003e13 Bridging LLMs to the real world with the Model Context Protocol\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eEbook License\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eEnd-User Warranty And License Agreement\u003c\/p\u003e\u003cp\u003e1. 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