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.
您将学到什么
Understand how to use llama.cpp Python APIs to build Llama 2-based large language model (LLM)applications.
Learn to run and interact with the Llama 2 large language model on commodity local hardware.
Learn to utilize zero- and few-shot prompting as well as advanced methods like grammars in llama.cpp to enhance and constrain Llama 2 model output.
Learn about the different Llama 2 model variants: the base model, chat model, and code llama and how to interact with these models in Python.
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3 项作业
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该课程共有3个模块
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.
涵盖的内容
6个视频4篇阅读材料1个作业1个讨论话题1个非评分实验室
This module unravels Llama 2's intricacies within Python, guiding you through tokenization, the development of Llama 2 applications via llama.cpp, and parameter adjustments for improved interactions.
涵盖的内容
4个视频1篇阅读材料1个作业1个非评分实验室
This module begins with a demonstration of zero and few-shot prompting techniques, then moves on to controlling model output for tailored responses. It culminates in practical programming assignments, enabling you to apply your knowledge and showcase your skills in crafting refined Llama 2 applications.
涵盖的内容
4个视频4篇阅读材料1个作业1个编程作业2个非评分实验室1个插件
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状态：预览Duke University
Duke University
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学生评论
19 条评论
- 5 stars
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- 4 stars
26.31%
- 3 stars
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已于 Feb 26, 2025审阅
Overall good course. The assignment is finicky due to the model used but overall great intro to llama.
已于 Jun 13, 2024审阅
Very good course to practice the prompting engineering
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