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Learn Hugging Face for Mastering Generative AI with LLMs
Rating: 4.4 out of 5(885 ratings)
5,648 students

Learn Hugging Face for Mastering Generative AI with LLMs

LLMs & Transformers in Hugging Face: Dive into Hugging Face, Fine-tuning, Tokenization, and Datasets
Created byTensor Teach
Last updated 5/2025
English

What you'll learn

  • How to build your own tokenizer using Hugging Face's Transformers library
  • How to build a custom dataset in Hugging Face
  • How to train a GPT-2 model from scratch using Hugging Face's Transformers library
  • How to instruction fine-tune a LLM using PEFT

Course content

5 sections21 lectures2h 0m total length
  • Understanding Large Language Models In Hugging Face6:42
  • Managing Compute Requirements For LLMs4:46

    Learn to manage compute for large language models by balancing 32-bit precision, memory demands, and small batch sizes during training.

  • What Is Hugging Face?3:26
  • Accessing Pre-Trained Models From Hugging Face: Hands-On Example6:06

    Access pre-trained models from Hugging Face using the transformers library and pipeline. Load GPT-2 tokenizer and model, then generate text and explore tokenizers, datasets, and generation parameters.

Requirements

  • Beginner python experience

Description

Welcome to "Learn Hugging Face for Mastering Generative AI with LLMs". In today's AI-driven world, Hugging Face has become a central platform for working with Large Language Models (LLMs), which have revolutionized generative AI by enabling machines to generate human-like text, answer questions, and even create original content. This course is meticulously designed to give you a deep understanding of these models and how to harness their power using Hugging Face.

Our journey begins with a robust introduction to LLMs, exploring their intricacies and how to manage their compute requirements, all within the Hugging Face ecosystem. From there, we dive into the world of Hugging Face, which provides an extensive collection of pre-trained models that can be applied in a wide range of innovative applications.

Practical knowledge is essential, so the course transitions into a deep dive into Transformers, a key technology behind LLMs, with a special focus on Hugging Face implementations. You'll get hands-on experience with Hugging Face tools, manipulating datasets, building custom models, and mastering tokenization.

Finally, we emphasize training, fine-tuning, and quantization, with models downloaded from Hugging Face. Learn how to adjust LLMs to your needs, whether for summarization or text generation. With techniques like Instruction Fine-tuning and PEFT, you'll master the art of fine-tuning models. We’ll even show you how to train a GPT-2 from scratch using Hugging Face to generate text from a custom dataset. Then finally, we will show you how to quantize your models so that they take up less memory.

Who this course is for:

  • Data Scientists learning to build their own models in Hugging Face
  • Generative AI enthusiasts that want to learn how to build & use their own custom models