Rapid Application Development Using Large Language Models (RADLLM)

Recent advancements in both the techniques and accessibility of large language models (LLMs) have opened up unprecedented opportunities for businesses to streamline their operations, decrease expen...

Recent advancements in both the techniques and accessibility of large language models (LLMs) have opened up unprecedented opportunities for businesses to streamline their operations, decrease expenses, and increase productivity at scale. Enterprises can also use LLM-powered apps to provide innovative and improved services to clients or strengthen customer relationships. For example, enterprises could provide customer support via AI virtual assistants or use sentiment analysis apps to extract valuable customer insights.

In this course, you’ll gain a strong understanding and practical knowledge of LLM application development by exploring the open-sourced ecosystem, including pretrained LLMs, that can help you get started quickly developing LLM-based applications.

Please note that once a booking has been confirmed, it is non-refundable. This means that after you have confirmed your seat for an event, it cannot be cancelled and no refund will be issued, regardless of attendance.

By participating in this workshop, you’ll learn how to:



- Find, pull in, and experiment with the HuggingFace model repository and the associated transformers API
- Use encoder models for tasks like semantic analysis, embedding, question-answering, and zero-shot classification
- Use decoder models to generate sequences like code, unbounded answers, and conversations
- Use state management and composition techniques to guide LLMs for safe, effective, and accurate conversation

Introduction



- Meet the instructor.
- Create an account at courses.nvidia.com/join
From Deep Learning to Large Language Models



- Learn how large language models are structured and how to use them:
- Review deep learning- and class-based reasoning, and see how language modeling falls out of it.
- Discuss transformer architectures, interfaces, and intuitions, as well as how they scale up and alter to make state-of-the-art LLM solutions.
Specialized Encoder Models



- Learn how to look at...