Selecting the Right LLM with Hugging Face
This course guides you through the Hugging Face Hub, teaching you how to evaluate and select the right Large Language Model (LLM) based on size, performance, specialization, licensing, and computational needs.
Overview
This course includes:
- 3 hours of on-demand video
- Certificate of completion
- Direct access/chat with the instructor
- 100% self-paced online
There are literally thousands of Large Language Models or LLMs available out there that can be used for a plethora of purposes. Hugging Face is the de-facto hub for language models, offering a huge collection where you can find and use almost any model you need. Choosing the right model can be an arduous task given models come in various shapes, sizes and configurations and each model is specialized at something different. So, when you approach Hugging Face in search of the right Model for your requirement, you have to know the art of this matchmaking.
In this course, we will learn how to navigate through the Hugging Face Hub for Models, matching their configurations to your needs. We will understand key characteristics of Models (LLMs), such as Size, Computational Requirements, Specializations, Licensing and so on. We will look into various families of Models and their specializations, performance and variants. We will also learn how to use various models from Hugging Face and Evaluate them based on your requirements.
Skills You Will Gain
Learning Outcomes (At the end of this program you will be able to)
- Navigate through the Hugging Face Ecosystem.
- Comparing Models using various Factors and Practical Considerations.
- Using a Model from Hugging Face.
- Determine the most suitable model for a given task by scoring the results from each candidate model on a variety of parameters.
Prerequisites
Participants should have a strong foundation in Python programming and a basic understanding of Large Language Models (LLMs) and their programmatic use, as the course will build on these concepts with practical coding exercises and advanced topics like model selection, comparison, and evaluation.
Who Should Attend
This course is designed for Data Scientists, ML Engineers, Software Developers and IT Engineers aiming to build their own LLM Applications, RAG Applications or Fine Tuned Models, equip the learners with the knowledge and skills necessary to find and use the right Models for their needs.
Curriculum
Instructors
Frequently Asked Questions
How much do the courses at Starweaver cost?
We offer flexible payment options to make learning accessible for everyone. With our Pay-As-You-Go plan, you can pay for each course individually. Alternatively, our Subscription-Based plan provides you with unlimited access to all courses for a monthly or yearly fee.
Do you offer any certifications upon completion of a course at Starweaver?
Yes, we do offer a certification upon completion of our course to showcase your newly acquired skills and expertise.
Does Starweaver offer any free courses or trials?
No, we don't offer any free courses, but we do offer 5-day trial only on our subscriptions-based plans.
Are Starweaver's courses designed for beginners or advanced students?
Our course is designed with three levels to cater to your learning needs - Core, Intermediate, and Advanced. You can choose the level that best suits your knowledge and skillset to enhance your learning experience.
What payment options are available for Starweaver courses?
We accept various payment methods such as major credit cards, PayPal, wire transfer, and company purchase orders. For more information related to payments contact customer support.
Do you offer refunds?
Yes, we do offer a 100% refund guarantee for our courses within a specified time frame. If you are not satisfied with the course, contact our customer support team to request a refund with your order details. Some restrictions may apply.
