Beginning Llamafile for Local Large Language Models (LLMs)
Learn to deploy and use local LLMs: Master Llamafile for private, efficient AI without cloud dependencies.
Learn to deploy and use local LLMs: Master Llamafile for private, efficient AI without cloud dependencies.
This course introduces learners to Llamafile, a powerful tool for running large language models (LLMs) locally. It focuses on practical skills for deploying and using LLMs without relying on cloud services, ensuring data privacy and reducing latency. The curriculum covers Llamafile's architecture, API usage, and integration with applications. Students will learn to create and customize Llamafiles, use the Mixtral model, and build portable binaries with Cosmopolitan. The course emphasizes hands-on experience, including running a Llamafile server and interacting with it using various tools.
Instructors:
English
Deutsch, हिन्दी, Русский, 17 more
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What you'll learn
Learn how to serve large language models as production-ready web APIs using the llama.cpp framework
Understand the architecture and capabilities of the llama.cpp example server for text generation, tokenization, and embedding extraction
Gain hands-on experience in configuring and customizing the server using command line options and API parameters
Master the process of creating and using Llamafiles for local LLM deployment
Learn to build portable binaries with Cosmopolitan for cross-platform compatibility
Understand how to interact with the Llamafile API using tools like curl and Python
Skills you'll gain
This course includes:
29 Minutes PreRecorded video
4 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There is 1 module in this course
This course provides a comprehensive introduction to using Llamafile for deploying and running large language models (LLMs) locally. It covers the fundamentals of Llamafile, its architecture, and practical applications. Students will learn how to create and customize Llamafiles, use the Mixtral model, and build portable binaries with Cosmopolitan. The course emphasizes hands-on experience, including setting up a Llamafile server, interacting with its API, and integrating LLM capabilities into applications. Through a combination of video lectures, readings, quizzes, and practical exercises, learners will gain the skills to deploy powerful language models as scalable web APIs while maintaining data privacy and reducing latency.
Getting Started with Mozilla Llamafile
Module 1 · 3 Hours to complete
Fee Structure
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Instructors
Executive in Residence and Founder of Pragmatic AI Labs
Noah Gift, founder of Pragmatic A.I. Labs, is a lecturer in the Duke MIDS Graduate Data Science Program, where he designs and teaches graduate courses on machine learning, MLOps, A.I., and data science. A Python Software Foundation Fellow and AWS Machine Learning Hero, he consults on machine learning and cloud architecture for students and faculty. He is the author of several books, including Practical MLOps, Python for DevOps, and Pragmatic A.I. With extensive experience across roles such as CTO, General Manager, Consulting CTO, Chief Data Scientist, and Cloud Architect, he has worked with leading companies like ABC, Caltech, Sony Imageworks, Disney Feature Animation, Weta Digital, AT&T, Turner Studios, and Linden Lab, spanning industries from television and film to SaaS and telecommunications. Gift has successfully launched globally scaled products that generated millions in revenue.
Adjunct Assistant Professor in the Pratt School of Engineering
Alfredo Deza is an Adjunct Assistant Professor in the Pratt School of Engineering at Duke University, where he teaches various courses, including machine learning and programming for graduate students. With a background as a former Olympic athlete, Deza brings a unique perspective to his teaching, emphasizing consistency and discipline. He has authored numerous online courses on platforms like Coursera, covering topics such as Python programming, data engineering, and large language models. In addition to his academic role, Deza works in developer relations at Microsoft, where he focuses on bridging technical concepts with practical applications. His commitment to education and innovation is evident in his efforts to create engaging learning experiences that keep pace with advancements in technology.
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