Efficient Large Language Model (LLM) Customization

Price
$500.00 USD

Duration
1 Day

Delivery Methods
Virtual Instructor Led
Private Group

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Course Overview

In this course, you'll go beyond using out-of-the-box pretrained LLMs and learn a variety of techniques to efficiently customize pretrained LLMs for your specific use cases—without engaging in the computationally intensive and expensive process of pretraining your own model or fine-tuning a model's internal weights. Using the open-source NVIDIA NeMo™ framework, you’ll learn prompt engineering and various parameter-efficient fine-tuning methods to customize LLM behavior for your organization.

Course Objectives

Use prompt engineering to improve the performance of pretrained LLMs
Apply various fine-tuning techniques with limited data to accomplish tasks specific to your use cases
Use a single pretrained model to perform multiple custom tasks
Leverage the NeMo framework to customize models like GPT, LLaMA-2, and Falcon with ease

Who Should Attend?

Highly-experienced Python Developers

Top-rated instructors: Our crew of subject matter experts have an average instructor rating of 4.8 out of 5 across thousands of reviews.
Authorized content: We maintain more than 35 Authorized Training Partnerships with the top players in tech, ensuring your course materials contain the most relevant and up-to date information.
Interactive classroom participation: Our virtual training includes live lectures, demonstrations and virtual labs that allow you to participate in discussions with your instructor and fellow classmates to get real-time feedback.
Post Class Resources: Review your class content, catch up on any material you may have missed or perfect your new skills with access to resources after your course is complete.
Private Group Training: Let our world-class instructors deliver exclusive training courses just for your employees. Our private group training is designed to promote your team’s shared growth and skill development.
Tailored Training Solutions: Our subject matter experts can customize the class to specifically address the unique goals of your team.

Course Prerequisites

Professional experience with the Python programming language
Familiarity with fundamental deep learning topics like model architecture, training, and inference
Familiarity with a modern Python-based deep learning framework (PyTorch preferred)
Familiarity working with out-of-the-box pretrained LLMs

Agenda

Introduction
Engineering Effective Prompts
Customized Prompt Learning
Parameter-Efficient Fine-Tuning (PEFT) and Supervised Fine-Tuning (SFT)
Assessment and Q&A

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