LinkedIn – Generative AI and Open Source Models: Hands-On Practice with Hugging Face Models 2024-9

Description

Generative AI and Open Source Models Course: Hands-On Practice with Hugging Face Models. Large-scale linguistic models (LLM) are becoming increasingly important in various industries. Learn about the importance of tokenization, special tokens, and chat patterns in text generation. Explore how to manipulate the next selected token and gain a technical and intuitive understanding of production parameters such as temperature, top-p, top-k, repetition penalty, length penalty and bad word list. Discover how these parameters can be combined to form powerful decoding strategies, including greedy search, polynomial sampling, beam search, and adversarial search. Get hands-on experience using the Hugging Face text generation API and get a glimpse into interacting with the NVIDIA NIM API to explore larger models. By the end of this course, you will have a solid foundation in controlling text production with LLMs and be able to apply these skills in real-world scenarios.

What you will learn

• Comprehensive understanding of how large language models work in text generation
• Learning tokenization techniques and using special tokens to control model output
• Familiarity with the key parameters of text production such as temperature, top-p, top-k and how they affect the output
• Explore different decoding strategies to control model output
• Hands-on experience using the Hugging Face text generation API
• A glimpse into interacting with the NVIDIA NIM API to explore larger models

This course is suitable for people who

• Interested in learning about generative artificial intelligence and large language models
• Want to gain a comprehensive understanding of how large language models work
• They want to learn how to use large language models to generate text
• Developers, researchers, and anyone looking to learn more about large language models

Course details

• Publisher: LinkedIn
• Lecturer: Harpreet Sahota
• Education level: Intermediate
• Training duration: 1 hour and 52 minutes

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