Introduction Hugging Face Llm Course

Leo Migdal

-Nov 6, 2025, 3:22 PM

and get access to the augmented documentation experience This course will teach you about large language models (LLMs) and natural language processing (NLP) using libraries from the Hugging Face ecosystem — 🤗 Transformers, 🤗 Datasets, 🤗 Tokenizers, and 🤗 Accelerate — as... We’ll also cover libraries outside the Hugging Face ecosystem. These are amazing contributions to the AI community and incredibly useful tools. While this course was originally focused on NLP (Natural Language Processing), it has evolved to emphasize Large Language Models (LLMs), which represent the latest advancement in the field. Throughout this course, you’ll learn about both traditional NLP concepts and cutting-edge LLM techniques, as understanding the foundations of NLP is crucial for working effectively with LLMs.

Master working with state-of-the art Large Lanaguage Models with Hugging Face’s powerful tools and libraries. Bringing real-world expertise from leading global companies Master's degree, Social Research Methods & Statistics Hugging Face is an essential toolkit for any developer working with state-of-the-art Large Language Models (LLMs). This course will introduce you to the powerful tools and libraries Hugging Face offers, from out-of-the-box solutions, to custom model training and configurations. Through engaging text and video lessons, interactive excersises and coding tutorials, you'll gain the practical skills needed to work confidently with Hugging Face.

Understand LLM capabilities like summarization and content translation Build real-world applications using chatbots, virtual assistants, and sentiment analysis Evaluate LLM performance using ROUGE, GLUE, SuperGLUE, and BIG-bench benchmarks Analyze industry use cases and deployment strategies for LLM-powered solutions This comprehensive course on Generative AI using Hugging Face equips you with the skills to build real-world NLP applications powered by transformer models. Begin with an introduction to the Hugging Face ecosystem and its role in accelerating AI development.

Gain hands-on experience with speech-to-text pipelines and learn how to convert audio into accurate transcripts using pre-trained models. Progress to building sentiment analysis tools that interpret user feedback and classify emotions from text data. Advance your skills in natural language generation by leveraging Hugging Face's pre-trained transformers to create human-like content at scale, ideal for chatbots, summaries, and automated writing. Welcome to a beginner-friendly, well-structured set of notes for the Hugging Face LLM Course! 🎉 These notes guide you from zero to advanced in Natural Language Processing (NLP) and Large Language Models (LLMs) using the Hugging Face ecosystem. Perfect for newcomers and enthusiasts alike!

💡 Feel free to open issues or submit pull requests to improve the notes! Join the Hugging Face Discord for community support 💬. This repository is licensed under the MIT License. See LICENSE for details. Share what you’ve learned, and be a standout professional in your desired industry with a certificate showcasing your knowledge gained from the course.

Showcase on your LinkedIn profile under “Licenses and Certificate” section Download or print out as PDF to share with others Share as image online to demonstrate your skill Use your iOS or Android LinkedIn Learning app, and watch courses on your mobile device without an internet connection. Learn about the Hugging Face AI and machine learning platform, and how their tools can streamline ML and AI development. Hugging Face is an organization at the center of the open-source ML/AI ecosystem.

Developers use their libraries to easily work with pre-trained models, and their Hub platform facilitates sharing and discovery of models and datasets. In this course, you’ll learn about the tools Hugging Face provides for ML developers, from fine-tuning models to hosting your own ML-powered app demos. Learn about the Hugging Face platform for ML/AI. Hugging Face is an organization working to democratize good machine learning. Large Language Models are revolutionizing the way that we interact with technology. From generating human-like text to powering chatbots, translating languages, and even writing code, LLMs are at the forefront of artificial intelligence.

But how can beginners get started with these powerful models? Here comes Hugging Face, a powerful open source community and platform that makes working with LLMs accessible, fun, and intuitive. Let's explore what LLMs are, why hugging-face is a game-changer, and how you can start using it to build your own AI-powered applications. and get access to the augmented documentation experience Welcome to the Hugging Face course! This introduction will guide you through setting up a working environment.

If you’re just starting the course, we recommend you first take a look at Chapter 1, then come back and set up your environment so you can try the code yourself. All the libraries that we’ll be using in this course are available as Python packages, so here we’ll show you how to set up a Python environment and install the specific libraries you’ll need. We’ll cover two ways of setting up your working environment, using a Colab notebook or a Python virtual environment. Feel free to choose the one that resonates with you the most. For beginners, we strongly recommend that you get started by using a Colab notebook. Note that we will not be covering the Windows system.

If you’re running on Windows, we recommend following along using a Colab notebook. If you’re using a Linux distribution or macOS, you can use either approach described here.

Introduction Hugging Face Llm Course

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💡 Feel Free To Open Issues Or Submit Pull Requests