Local LLMs with llamafile

Duke University, located in Durham, United States, is a historic institution founded in 1838. As an international student, you'll find many advantages to studying here, including access to a diverse community of 3584 international students, a broad academic offering, and a unique blend of tradition and innovation. Specifically, you'll benefit from the university's strong research focus and its location in the heart of North Carolina's Research Triangle.

Duke University offers 213 programs, with many focusing on engineering, business, and medicine. The university is particularly renowned for its departments of engineering and environmental sciences, which provide opportunities for you to engage in cutting-edge research. English is the primary language of instruction, but you'll also have the chance to learn other languages, such as Spanish, Chinese, and Arabic, through the university's language programs.

As a student, you'll have access to modern facilities, including libraries, labs, and recreational centers. The campus is situated in a charming city with a rich cultural scene, offering many opportunities for you to explore and engage with the local community. For instance, you can visit the nearby Durham Performing Arts Center or take part in the city's annual festivals, which celebrate music, food, and art. With many student clubs and organizations available, you'll find plenty of ways to get involved and make the most of your time at Duke University.

The Local LLMs with llamafile program at Duke University is a non-degree, project-based course that lasts one hour. It teaches students to package open-source AI models into portable llamafile executables and deploy them locally across Windows, macOS, and Linux. The course is online and requires no prior education.

The curriculum focuses on packaging AI models, deploying llamafiles, monitoring system metrics, and querying llamafile APIs with Python. Students gain hands-on experience with real-time inference through examples. The course helps students develop skills in AI model deployment, system metrics monitoring, and Python programming.

After completing the program, students can pursue careers as AI Engineers, Software Developers, Data Scientists, Machine Learning Engineers, or Research Scientists. They can work in industries like technology, research, and finance, and for employers like Microsoft, Google, or Facebook.