We may earn an affiliate commission when you visit our partners.
Course image
Noah Gift and Alfredo Deza

Master Local Large Language Models (LLMs) Deployment

  • Unlock the power of cutting-edge LLMs on your machine
  • Learn to set up & interact with LLMs via intuitive web interfaces & APIs
  • Explore tools like Hugging Face & Mozilla for seamless LLM integration

Course Highlights:

Read more

Master Local Large Language Models (LLMs) Deployment

  • Unlock the power of cutting-edge LLMs on your machine
  • Learn to set up & interact with LLMs via intuitive web interfaces & APIs
  • Explore tools like Hugging Face & Mozilla for seamless LLM integration

Course Highlights:

  • Gain solid understanding of running LLMs locally
  • Set up local environment with powerful tooling for different LLMs
  • Interact with LLMs through web interfaces & API access
  • Leverage programming languages for efficient LLM integration
  • Use Hugging Face Candle & Mozilla llamafile for LLM capabilities

Develop invaluable skills for efficient local deployment of LLMs. Master setup, integration & interaction techniques to leverage the full potential of large language models on your machine.

What's inside

Learning objectives

  • Tools for running llms locally like llamafile.
  • Local large language models (llms)
  • Use the python apis to interact with local llms

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides hands-on experience with cutting-edge Large Language Models (LLMs)
Develops proficiency in setting up and interacting with LLMs through web interfaces and APIs
Enhances understanding of local deployment of LLMs, empowering learners to leverage their full potential
Utilizes industry-standard tools like Hugging Face and Mozilla for seamless LLM integration
Facilitates efficient LLM integration through programming languages

Save this course

Save Applied Local Large Language Models to your list so you can find it easily later:
Save

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Applied Local Large Language Models with these activities:
Review Python APIs
Cover Python APIs before beginning the course to help prepare for upcoming content.
Browse courses on Python
Show steps
  • Revisit basic Python syntax and data structures.
  • Review the use of Python libraries and modules.
  • Practice using Python APIs for data manipulation and analysis.
Practice using the web-interface to interact with LLM
Helps solidify what has been learned in the lecture
Browse courses on Web Interface
Show steps
  • Open a web-based LLM interface
  • Use the interface to ask questions and get responses
  • Experiment with different prompts and parameters
Follow a tutorial on using Hugging Face
Helps students learn how to use Hugging Face library
Browse courses on Hugging Face
Show steps
  • Find a tutorial on Hugging Face
  • Follow the tutorial step-by-step
  • Use Hugging Face to complete the tasks in the tutorial
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Implement LLMs in Python
Reinforce comprehension of LLM implementation with hands-on practice.
Browse courses on Python
Show steps
  • Set up a local development environment with necessary libraries.
  • Develop code to interact with LLMs using Python APIs.
  • Test and debug code to ensure accurate LLM integration.
Explore LLMs with Hugging Face
Provide students with additional resources to explore LLMs and their capabilities.
Browse courses on LLMs
Show steps
  • Find and review tutorials on Hugging Face website and documentation.
  • Follow tutorials to set up and interact with LLMs using Hugging Face.
  • Utilize Hugging Face's tools and resources to enhance understanding.
LLM Use Case Presentation
Encourage students to demonstrate their understanding by creating presentations on LLM use cases.
Browse courses on LLMs
Show steps
  • Research and identify a specific LLM use case.
  • Develop a presentation outlining the use case, benefits, and potential applications.
  • Present the use case to the class or a small group.
Build a simple chatbot using a LLM
Helps students combine everything they learned to build a real-world project
Browse courses on LLM
Show steps
  • Design the chatbot
  • Gather the necessary data
  • Train the LLM
  • Deploy the chatbot
Local LLM Deployment Project
Challenge students to apply their knowledge in a practical setting, fostering deeper understanding.
Browse courses on LLMs
Show steps
  • Define a project scope and objectives.
  • Gather and prepare data for LLM training.
  • Train and fine-tune a local LLM model.
  • Deploy the trained LLM model locally.
  • Evaluate the performance and accuracy of the deployed LLM.
Community Outreach with LLMs
Provide students with an opportunity to apply their LLM knowledge and skills to make a positive social impact.
Browse courses on LLMs
Show steps
  • Identify a community organization or project that could benefit from LLM applications.
  • Develop a plan for using LLMs to address a specific need or challenge faced by the organization.
  • Volunteer time to implement the plan and provide LLM-based support.
Hackathon: LLM Innovation
Challenge students to push their limits and collaborate on innovative LLM projects.
Show steps
  • Form teams and brainstorm ideas for LLM-based projects.
  • Develop and implement LLM solutions within the hackathon time frame.
  • Present project results and demonstrate the potential of LLMs.

Career center

Learners who complete Applied Local Large Language Models will develop knowledge and skills that may be useful to these careers:
Natural Language Processing Engineer
Natural Language Processing Engineers develop and maintain software systems that can understand and generate human language. This course can help you build a strong foundation in natural language processing, which is essential for success in this role. You will learn about the different types of natural language processing tasks, how to build natural language processing models, and how to evaluate natural language processing models. This course will also give you hands-on experience with popular natural language processing tools and frameworks.
Machine Learning Engineer
Machine Learning Engineers are responsible for developing, deploying, and maintaining machine learning models. This course can help you build a strong foundation in machine learning, which is essential for success in this role. You will learn about the different types of machine learning models, how to train and evaluate them, and how to deploy them into production. This course will also give you hands-on experience with popular machine learning tools and frameworks.
Computational Linguist
Computational Linguists use computational methods to study human language. This course can help you build a strong foundation in computational linguistics, which is essential for success in this role. You will learn about the different types of computational linguistics tasks, how to develop computational linguistics models, and how to evaluate computational linguistics models. This course will also give you hands-on experience with popular computational linguistics tools and frameworks.
Data Scientist
Data Scientists use data to solve business problems. This course can help you build a strong foundation in data science, which is essential for success in this role. You will learn about the different types of data science techniques, how to collect and clean data, and how to analyze and interpret data. This course will also give you hands-on experience with popular data science tools and frameworks.
Software Engineer
Software Engineers design, develop, and maintain software systems. This course can help you build a strong foundation in software engineering, which is essential for success in this role. You will learn about the different stages of the software development lifecycle, how to design and implement software systems, and how to test and deploy software systems. This course will also give you hands-on experience with popular software engineering tools and frameworks.
Product Manager
Product Managers are responsible for the development and marketing of software and hardware products. This course can help you develop the skills you need to be successful in this role, such as how to develop product roadmaps, how to conduct market research, and how to launch new products. This course will also give you hands-on experience with popular product management tools and frameworks.
Technical Writer
Technical Writers create and maintain documentation for software and hardware products. This course can help you develop the skills you need to be successful in this role, such as how to write clear and concise technical documentation, how to use technical writing tools, and how to collaborate with other technical writers. This course will also give you hands-on experience with popular technical writing tools and frameworks.
Business Analyst
Business Analysts help businesses improve their operations by analyzing data and identifying opportunities for improvement. This course can help you develop the skills you need to be successful in this role, such as how to collect and analyze data, how to identify and solve business problems, and how to communicate your findings to stakeholders.
User Experience Designer
User Experience Designers design and evaluate user interfaces for software and hardware products. This course can help you develop the skills you need to be successful in this role, such as how to design user-centered interfaces, how to conduct user research, and how to evaluate user interfaces. This course will also give you hands-on experience with popular user experience design tools and frameworks.
Consultant
Consultants provide advice and guidance to businesses on a variety of topics, including technology, strategy, and operations. This course can help you develop the skills you need to be successful in this role, such as how to identify and solve business problems, how to communicate your findings to stakeholders, and how to build and maintain client relationships.
Entrepreneur
Entrepreneurs start and operate their own businesses. This course can help you develop the skills you need to be successful in this role, such as how to develop a business plan, how to raise capital, and how to market your products or services. This course will also give you hands-on experience with popular entrepreneurial tools and resources.
Teacher
Teachers educate students in a variety of subjects. This course can help you develop the skills you need to be successful in this role, such as how to plan and deliver lessons, how to assess student learning, and how to create a positive learning environment. This course will also give you hands-on experience with popular educational tools and resources.
Librarian
Librarians provide access to information and resources to the public. This course can help you develop the skills you need to be successful in this role, such as how to organize and catalog information, how to conduct research, and how to provide reference services. This course will also give you hands-on experience with popular library tools and resources.
Archivist
Archivists preserve and manage historical documents and artifacts. This course can help you develop the skills you need to be successful in this role, such as how to appraise and accession historical documents, how to catalog and store historical artifacts, and how to provide access to historical materials. This course will also give you hands-on experience with popular archival tools and resources
Museum curator
Museum Curators manage and exhibit museum collections. This course can help you develop the skills you need to be successful in this role, such as how to appraise and acquire museum objects, how to design and install museum exhibits, and how to provide educational programs to the public. This course will also give you hands-on experience with popular museum tools and resources.

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Applied Local Large Language Models.
Offers a comprehensive introduction to deep learning, providing a solid background for understanding the underlying principles and techniques used in LLMs. It also delves into practical implementation using Python, complementing the course's focus on local deployment.
Provides a comprehensive overview of speech and language processing, offering valuable background knowledge for understanding the context and applications of LLMs. It covers fundamental concepts, algorithms, and applications, enhancing the course's relevance to the broader field of natural language processing.
Offers a comprehensive overview of natural language processing techniques and applications using Python. It provides a solid foundation for understanding the practical implementation of LLMs, complementing the course's emphasis on local deployment.
Offers a comprehensive overview of the fundamental principles and algorithms of deep learning. It provides a solid theoretical foundation for understanding the underlying concepts behind LLMs, enhancing the course's ability to delve into advanced topics.
Covers the fundamentals of deep learning for natural language processing. Provides a comprehensive overview of the field, including techniques for text classification, machine translation, and question answering.
A classic textbook on statistical learning. Provides a comprehensive overview of the field, including topics such as linear regression, logistic regression, and decision trees.
A comprehensive textbook on machine learning from a probabilistic perspective. Provides a thorough understanding of the theory and algorithms used in machine learning.
A comprehensive textbook on numerical optimization. Provides a thorough understanding of the theory and algorithms used in numerical optimization.
A comprehensive textbook on convex optimization. Provides a thorough understanding of the theory and algorithms used in convex optimization.
A practical guide to deep learning for coders. Provides hands-on tutorials for a variety of deep learning tasks, including natural language processing.
A friendly introduction to deep learning. Provides a clear and concise overview of the field, without getting bogged down in technical details.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to Applied Local Large Language Models.
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2024 OpenCourser