Beginning Llamafile
Learn to deploy and serve language models through REST APIs using llama.cpp server, enabling private, efficient, and cost-effective NLP solutions
Learn to deploy and serve language models through REST APIs using llama.cpp server, enabling private, efficient, and cost-effective NLP solutions
This practical course teaches you how to harness the power of large language models through API endpoints using the llama.cpp server. You'll learn to configure model behavior, handle requests efficiently, and integrate language model capabilities into applications. The course covers installation of Cosmopolitan Libc toolkit, local model deployment with llamafile, and API interaction for NLP tasks. With hands-on exercises and code examples, you'll master serving language models in production environments.
Instructors:
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What you'll learn
Install and configure the Cosmopolitan Libc toolkit
Deploy language models locally using llamafile
Create portable command-line interfaces
Implement REST API endpoints for NLP tasks
Configure and optimize model serving behavior
Skills you'll gain
This course includes:
PreRecorded video
Quizzes, Ungraded Labs, Discussion Prompts
Access on Mobile, Tablet, Desktop
Limited Access access
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There is 1 module in this course
The course focuses on practical implementation of language model deployment using llamafile. Students learn to work with the Cosmopolitan Libc toolkit for creating portable applications, understand llamafile packaging and licensing, and develop REST API endpoints for language model serving. The curriculum covers system metrics monitoring, server configuration, and hands-on experience with tools like curl and Python for API interaction.
Getting Started with Mozilla Llamafile
Module 1
Fee Structure
Instructors
20 Courses
Pioneering Tech Leader & AI Educator Shaping the Future of Machine Learning
Noah Gift is a distinguished technology leader and founder of Pragmatic AI Labs with a remarkable 30-year career spanning film, TV, telecom, social networks, startups, and big data, currently serving as an Executive-in-Residence at Duke University. As an AWS ML Hero and Python Software Foundation Fellow, he has authored best-selling books through O'Reilly and Pearson on DevOps, MLOps, data engineering, and cloud computing that are widely adopted by major universities. His expertise in MLOps, data engineering, cloud architecture, and Rust programming has led him to teach thousands of students across prestigious institutions including Duke, Northwestern, UC Berkeley, University of San Francisco, and UC Davis, while also collaborating with Caltech and JPL on automated IT systems. Gift's impact extends beyond academia through his work as a startup CTO, his role in developing scalable distributed systems, and his contributions as a keynote speaker at conferences focused on cloud development and ethical AI use, holding certifications from AWS, Google, and Microsoft, and having published over 100 technical works while conducting workshops for organizations like NASA, PayPal, and PyCon.
20 Courses
A Technology Educator and Former Olympic Athlete Pioneering AI Innovation
Alfredo Deza embodies a unique combination of athletic excellence and technological expertise, transitioning from a distinguished career as Peru's first World Junior Champion in high jump and 2004 Olympian to becoming a leading voice in technology education and development. Currently serving as a Principal Cloud Advocate at Microsoft and Adjunct Assistant Professor at Duke University's Pratt School of Engineering, Deza has built an impressive career spanning nearly two decades in software engineering and education. His academic contributions extend through guest lectures at prestigious institutions including Oxford University, Georgia Tech, and Carnegie Mellon University, where he shares expertise in machine learning, cloud computing, and programming languages. As an accomplished author, he has co-authored several influential books with O'Reilly Media, including "Practical MLOps" and "Python for DevOps," while developing comprehensive courses on Coursera covering topics from large language models to Rust programming. His teaching portfolio at Duke includes graduate-level courses in machine learning operations and Python programming, reflecting his commitment to making complex technical concepts accessible. Deza's expertise encompasses a broad spectrum of technologies, including Azure, MLOps, DevOps, Python, Rust, and Databricks, which he leverages to bridge the gap between academic theory and industry practice. His unique perspective, shaped by his background as an Olympic athlete, influences his approach to teaching and technology, emphasizing the importance of continuous learning and knowledge sharing in the rapidly evolving field of artificial intelligence and cloud computing.
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