Llama for Python Programmers is designed for programmers who want to leverage the Llama 2 large language model (LLM) and take advantage of the generative artificial intelligence (AI) revolution. In this course, you’ll learn how open-source LLMs can run on self-hosted hardware, made possible through techniques such as quantization by using the llama.cpp package. You’ll explore how Meta’s Llama 2 fits into the larger AI ecosystem, and how you can use it to develop Python-based LLM applications. Get hands-on skills using methods such as few-shot prompting and grammars to improve and constrain Llama 2 output, allowing you to get more robust data interchanges between Python application code and LLM inference. Lastly, gain insight into the different Llama 2 model variants, how they were trained, and how to interact with these models in Python.
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Llama for Python Programmers is designed for programmers who want to leverage the Llama 2 large language model (LLM) and take advantage of the generative artificial intelligence (AI) revolution. In this course, you’ll learn how open-source LLMs can run on self-hosted hardware, made possible through techniques such as quantization by using the llama.cpp package. You’ll explore how Meta’s Llama 2 fits into the larger AI ecosystem, and how you can use it to develop Python-based LLM applications. Get hands-on skills using methods such as few-shot prompting and grammars to improve and constrain Llama 2 output, allowing you to get more robust data interchanges between Python application code and LLM inference. Lastly, gain insight into the different Llama 2 model variants, how they were trained, and how to interact with these models in Python.
Llama for Python Programmers is designed for programmers who want to leverage the Llama 2 large language model (LLM) and take advantage of the generative artificial intelligence (AI) revolution. In this course, you’ll learn how open-source LLMs can run on self-hosted hardware, made possible through techniques such as quantization by using the llama.cpp package. You’ll explore how Meta’s Llama 2 fits into the larger AI ecosystem, and how you can use it to develop Python-based LLM applications. Get hands-on skills using methods such as few-shot prompting and grammars to improve and constrain Llama 2 output, allowing you to get more robust data interchanges between Python application code and LLM inference. Lastly, gain insight into the different Llama 2 model variants, how they were trained, and how to interact with these models in Python.
This course does not require a data science or statistics background. It is developed specifically for Python application developers who are interested in integrating generative AI, such as Llama 2, into their work.
What's inside
Syllabus
Introduction to Llama 2: A High Quality Open Source Large Language Model
This module introduces you to Llama 2, highlighting its architecture, training method, and capabilities as a high-quality open-source LLM. This foundational segment prepares you for hands-on learning in the following modules.
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Syllabus
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Activities
Review Python basics
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Reviewing Python basics will help you understand the concepts of Llama 2 and generative AI more easily.
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Python Basics
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Go over Python syntax and data structures.
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Solve simple Python coding challenges.
Mentor other students who are learning about Llama 2
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Mentoring others will reinforce your understanding of Llama 2 and help you develop your communication skills.
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Mentoring
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Identify a student who is interested in learning about Llama 2.
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Share your knowledge and experience with the student.
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Provide guidance and support as they progress.
Show all two activities
Review Python basics
Show steps
Reviewing Python basics will help you understand the concepts of Llama 2 and generative AI more easily.
Browse courses on
Python Basics
Show steps
- Go over Python syntax and data structures.
- Solve simple Python coding challenges.
Mentor other students who are learning about Llama 2
Show steps
Mentoring others will reinforce your understanding of Llama 2 and help you develop your communication skills.
Browse courses on
Mentoring
Show steps
- Identify a student who is interested in learning about Llama 2.
- Share your knowledge and experience with the student.
- Provide guidance and support as they progress.
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