DeepSeek: Ollama Julia Anything LLM | Local LLM Setup & Julia Coding Examples
Playlists:
• Install Julia on Ubuntu: Quick and Easy
• How to Plot in Julia
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Welcome to this comprehensive tutorial on setting up and using local Large Language Models (LLMs) for coding in the Julia programming language! In this video, titled "DeepSeek: Ollama Julia Anything LLM", I’ll walk you through the entire process of installing and configuring powerful tools like Ollama, LM Studio, and Anything LLM to run LLMs locally on your machine. Whether you're a Julia developer, a machine learning enthusiast, or just curious about leveraging AI for coding, this video is packed with actionable insights and step-by-step instructions to help you get started.
00:00 Introduction: Local LLMs & Julia Programming
00:58 What is Ollama? (Local LLM Deployment Platform)
01:47 Ollama Installation Guide & Models
02:41 DeepSeek R1 LLM Overview
03:11 Running DeepSeek R1 with Ollama CLI
04:56 Anything LLM Installation & Features
05:39 Setting up Anything LLM Workspace with Ollama
09:41 Introducing LM Studio
11:09 Chatting with Local Models using LM Studio
13:08 Integrating Ollama/LM Studio with VS Code (Continue Extension)
14:15 Julia Code Generation Example (GLMakie Plotting)
16:26 Advanced Julia Plotting & Debugging
18:24 LLM Prompt Engineering for Code
20:40 Conclusion
What You’ll Learn in This Video
Installing Ollama: Discover how to set up Ollama, a versatile tool that allows you to run LLMs locally with ease.
LM Studio Setup: Learn how to install and configure LM Studio, a user-friendly interface for interacting with local LLMs.
Anything LLM Installation: Explore how to set up Anything LLM, a powerful platform for managing and interacting with multiple LLMs.
Downloading LLMs Locally: I’ll show you how to download and run models like DeepSeek, Qwen Coder, and Llama on your machine, ensuring you have the right tools for coding and development.
VS Code Integration: See how to use a specific VS Code extension to interact with these LLMs directly in your development environment, streamlining your workflow.
Julia Programming Examples: I’ll provide multiple examples of how to use these LLMs for coding in Julia, including code generation, debugging, and optimization tips.
Why This Video is a Must-Watch
If you’re looking to harness the power of AI for coding, this video is your ultimate guide. By running LLMs locally, you gain full control over your data and avoid relying on cloud-based services. Plus, integrating these models into your Julia development workflow can significantly boost your productivity and creativity.
Key Tools and Models Covered
Ollama: A lightweight tool for running LLMs locally.
LM Studio: A desktop app for experimenting with local LLMs.
Anything LLM: A platform for managing and interacting with multiple LLMs.
DeepSeek, Qwen Coder, and Llama Models: State-of-the-art LLMs optimized for coding tasks.
VS Code Extension: A powerful tool for integrating LLMs into your development environment.
Julia Coding Examples
I’ll demonstrate how to use these LLMs for various Julia programming tasks, such as:
Generating Julia code snippets for specific tasks.
Debugging and optimizing existing Julia code.
Exploring advanced Julia features with the help of AI.
Automating repetitive coding tasks using LLM-powered tools.
Optimized for YouTube Search
This video is optimized for YouTube search engines, ensuring you can easily find it using keywords like DeepSeek, Ollama, Julia, Anything LLM, LM Studio, Llama Models, Qwen Coder, and VS Code Extension. Whether you're searching for tutorials on local LLM setup, Julia programming, or AI-powered coding tools, this video has you covered.
Who is This Video For?
Julia developers looking to enhance their coding workflow with AI.
Machine learning enthusiasts interested in running LLMs locally.
Programmers curious about integrating LLMs into their development environment.
Anyone interested in exploring the intersection of AI and programming.
Don’t forget to like, comment, and subscribe for more tutorials on AI, programming, and cutting-edge tools. If you have any questions or need further clarification, drop a comment below, and I’ll be happy to help!