LLMs in Practice: Building with Hugging Face

Teacher

Mode

Offline / Online / Weekend

Duration

6 Hours

Who Should Enroll

This course is ideal for working professionals, college students, developers, and data enthusiasts who are interested in learning how to build and deploy models using Hugging Face and related technologies.

Prerequisites

No prior knowledge is needed. Basic understanding of programming and familiarity with APIs is helpful.

Program Objectives

The goal of this course is to provide participants with practical skills for working with large language models (LLMs) using Hugging Face. The course will cover accessing models through the Hugging Face API, utilizing GPT-like APIs for content generation, and building interactive chatbots or assistants using Chainlit. Additionally, participants will learn how to deploy models and APIs in cloud environments, enhancing their practical knowledge of LLMs.

Learning Objectives

Learn how to work with the Hugging Face API for model access and integration.
Understand how to use GPT-like APIs for generating content.
Develop an interactive chatbot or assistant using Chainlit.
Gain experience in deploying models and APIs in cloud environments.
Familiarize with tools such as Chainlit, Hugging Face, OpenAI API, Python, and REST API.

Key Topics

Working with Hugging Face API: Accessing and integrating models through the Hugging Face API.
Using GPT-like APIs for Content Generation: Applying GPT-like APIs for generating text and content.
Building an Interactive Chatbot or Assistant: Developing a functional chatbot or assistant using Chainlit.
Deploying Models and APIs in Cloud Environments: Techniques and best practices for deploying models and APIs on cloud platforms.
Tools Used: Chainlit, Hugging Face, OpenAI API, Python, REST API.

Faculty and Resources

The course is taught by experienced professionals with expertise in large language models and practical application development. Participants will have access to relevant tools and resources for hands-on learning and practice.