Ementorhub

What you'll learn

Sought-after job-ready skills businesses need for working with transformer-based LLMs for generative AI engineering... in just 1 week.

How to perform parameter-efficient fine-tuning (PEFT) using LoRA and QLoRA

How to use pretrained transformers for language tasks and fine-tune them for specific tasks.

How to load models and their inferences and train models with Hugging Face.

Skills you'll gain

PyTorch (Machine Learning Library)

Applied Machine Learning

Prompt Engineering

Large Language Modeling

Performance Tuning

Application Frameworks

Natural Language Processing

Generative AI

There are 2 modules in this course

During this course, you’ll explore transformers, model frameworks, and platforms such as Hugging Face and PyTorch. You’ll begin with a general framework for optimizing LLMs and quickly move on to fine-tuning generative AI models. Plus, you’ll learn about parameter-efficient fine-tuning (PEFT), low-rank adaptation (LoRA), quantized low-rank adaptation (QLoRA), and prompting. Additionally, you’ll get valuable hands-on experience in online labs that you can talk about in interviews, including loading, pretraining, and fine-tuning models with Hugging Face and PyTorch. If you’re keen to take your AI career to the next level and boost your resume with in-demand gen AI competencies that catch the eye of an employer, ENROLL today and have job-ready skills you can use straight away within a week!

Parameter Efficient Fine-Tuning (PEFT)