Description
Introduction to Llama. This course provides a hands-on look at the open-source Llama language models, how to deploy them on local infrastructure, and build AI applications with complete privacy. As the most popular large-scale open-source language model, Llama is the focus of this course, which aims to empower professionals to run Meta models on local hardware and solve the challenges of high cloud API costs and privacy concerns. The course begins with an overview of the history and evolution of the Llama family and key licensing considerations. It then moves into the practical part, showing how to run models like Llama 3.1 8B locally with tools like Ollama to leverage conventional GPUs, and integrate them into Python applications. The course also covers advanced concepts such as retrieval-augmented generation (RAG) systems, which allow a model to respond to specific documents without the need for retraining, and provides a comparative analysis of the fine-tuning approach and RAG. In the end, participants will gain the knowledge and skills necessary to implement autonomous and secure AI infrastructures.
What you will learn
- Running Models Locally: Learn how to set up and run Llama models on your own hardware without the need for cloud services.
- Evolution of the Llama family: Learn about the growth path of these models and understand the technical differences between the different versions.
- License Management: A detailed review of the legalities and licenses for commercial use of Meta’s open source models.
- Working with Ollama: Mastering the Ollama tool for optimal management of language models on GPUs.
- Programming and Integration: How to connect large language models to Python code to build intelligent software.
- RAG system implementation: Building question and answer systems that have the ability to understand and analyze user text documents.
- Optimization Strategies: Learn the difference between customizing the model through fine-tuning and using information retrieval methods.
- Security and privacy: Design architectures that keep data completely within the organization’s infrastructure.
This course is suitable for people who:
- Software developers: People who want to add AI capabilities to their applications.
- Artificial Intelligence and Machine Learning Engineers: Professionals looking to work with open source models and reduce processing costs.
- Technology and infrastructure managers: Those responsible for maintaining data security and deploying intelligent systems in isolated environments.
- Data analysts: People who need to analyze large volumes of organizational documents using artificial intelligence.
- Knowledge-based companies: Organizations that cannot use external APIs due to sanctions or privacy restrictions.
- Students and researchers: Enthusiasts who want to learn about the architecture and how Meta’s models work.
Introduction to Llama course details
- Publisher: Pluralsight
- Instructor: Dan Tofan
- Training level: Beginner
- Training duration: 1 hour and 5 minutes
Course headings
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: English
Quality: 720p
Download link
Downloadly
Rapidgator link
File(s) password: www.downloadly.ir
File size
120 MB
