Q3,Q4,Q5 - Class -09:Running Llama 3.1 with Ollama: A Comprehensive Guide for Local and Colab

👋 Hey AI Enthusiasts! Dive into the world of large language models with this in-depth tutorial. Learn how to effortlessly run Llama 3.1, a powerful language model, both on your local machine and on Google Colab. Discover the benefits of each environment and master the art of connecting them seamlessly.

This video covers:

Local Machine Setup: Setting up Llama 3.1 and Ollama on your local machine.
Google Colab Integration: Running Llama 3.1 on Google Colab.
Connecting Local and Colab: Establishing a smooth connection between your local machine and Google Colab.
Ngrok Tunnel: Creating a secure tunnel to access your local machine from Google Colab.
Whether you're a seasoned developer or just starting your journey with AI, this video provides clear instructions and practical demonstrations to help you get the most out of Llama 3.1.

📚 What Will You Learn? in this course
● Custom GPTs and Multi AI Agent Systems: Learn to fine-tuning foundational AI models, and market them in GPT stores. Learn key principles of designing effective AI agents, and organising a team of AI agents to perform complex, multi-step tasks. Apply these concepts to automate common business processes.
● Develop AI Powered Microservices: Master Python, build APIs using FastAPI, SQLModel, Postgres, Kafka, Kong, and leverage cutting-edge GenAI APIs like OpenAI, and Open Source AI LLMs.
● Cloud Native Expertise: Design and deploy cloud-native applications using Docker, DevContainers, TestContainers, Kubernetes, Terraform, and GitHub Actions.
● Distributed System Design: Designing systems that run on multiple computers (or nodes) simultaneously, interacting and coordinating their actions by passing messages over a network.
● Designing AI Solutions using Design Thinking and Behaviour Driven Development (BDD): We will learn to leverage these methodologies to create AI solutions that are not only technically sound but also highly user-centric and aligned with real-world needs.
● Fine-Tuning Open-Source Large Language Models using PyTorch, and Fast AI: We will learn to fine-tuning of open-source Large Language Models (LLMs) like Meta LLaMA 3 using PyTorch and Fast AI, with a focus on cloud-native training and deployment. We will set up development environments, preprocess data, fine-tune models, and deploy them using cloud native platforms.
● Physical AI and Humanoid Robotics: We will learn to design, simulate, and deploy advanced humanoid robots capable of natural interactions.


🛠️ Tools & Technologies Covered:
Poetry
Python
FastAPI
Docker
Kafka
Kong
Pytorch
ROS2

📌 Useful Links:
https://github.com/panaversity/learn-...
www.piaic.org

📣 Stay Connected:
Don't forget to like this video 👍, subscribe 🔔, and share 💌 it with your friends and colleagues who are interested in Python development and data science!

🎓 Perfect for beginners and experienced developers looking to enhance their Python skills!

#generativeai #artificialintelligence #AI #LLM #machinelearning #technology #future #CPU #GPU #NPU #cloudcomputing #opensource

**Connect with the Instructors**: Have questions? Want to connect? Find us on LinkedIn:
[Zia Khan](  / ziaukhan  )
[Qasim Sir](  / sirqasim  )

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