Generative AI Engineering and Fine-Tuning Transformers

IBM via Coursera

Coursera based on 53 ratings

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Overview

The demand for technical gen AI skills is exploding. Businesses are hunting hard for AI engineers who can work with large language models (LLMs). This Generative AI Engineering and Fine-Tuning Transformers course builds job-ready skills that will power your AI career forward. During this course, youll explore transformers, model frameworks, and platforms such as Hugging Face and PyTorch. Youll begin with a general framework for optimizing LLMs and quickly move on to fine-tuning generative AI models. Plus, youll learn about...

Syllabus

Transformers and Fine-Tuning

In this module, you will be introduced to Fine Tuning. Youll get an overview of generative models and compare Hugging Face and PyTorch frameworks. Youll also gain insights into model quantization and learn to use pre-trained transformers and then fine-tune them using Hugging Face and PyTorch.

Parameter Efficient Fine-Tuning (PEFT)

In this module, you will gain knowledge about parameter efficient fine-tuning (PEFT) and also learn about adapters such as LoRA (Low-Rank Adaptation) and QLoRA (Quantized Low-Rank Adaptation). In hands-on labs you will train a base model and pre-train LLMs with Hugging Face.