Docker for The Absolute Beginners - Run LLMs with Docker Model Runner (No Python, PyTorch, or CUDA Required)

🧪 Docker Model Runner Lab for Free: https://kode.wiki/4qP9myB Learn how to run Large Language Models (LLMs) locally using Docker and eliminate dependency hell forever! This comprehensive tutorial covers Docker Model Runner, a game-changing tool that treats AI models as OCI artifacts. In this video, you'll learn: ✅Why running LLMs locally is challenging (CUDA versions, Python dependencies, PyTorch compatibility) ✅How Docker containers solve the dependency hell problem ✅What inference engines are and why they matter ✅How to pull, run, and deploy AI models without Python or ML libraries ✅Creating custom AI personas with system prompts ✅Deploying models in offline/air-gapped environments Perfect for DevOps engineers, ML engineers, data scientists, and developers who want to streamline AI model deployment and ensure consistency across machines. ⏰ TIMESTAMPS: 00:00 - Introduction: The LLM Dependency Challenge 01:32 - Dependency Hell Explained 01:57 - How Docker Solves Dependency Management 02:49 - Understanding Inference Engines 03:40 - DevOps and MLOps Benefits 04:20 - Free Lab Introduction 05:01 - Task 1: Installing Docker Model Plugin 05:46 - Task 2: Pulling AI Models as OCI Artifacts 06:31 - Task 3: Testing Models Interactively 07:03 - Task 4: Starting Background Inference Service 07:31 - Task 5: Querying via OpenAI API 08:17 - Task 6: Creating Custom Personas 09:00 - Task 7: Packaging for Offline Deployment 09:59 - Conclusion and Next Steps 🧪 Docker Model Runner Lab for Free: https://kode.wiki/4qP9myB #Docker #LLM #DockerModelRunner #AIDeployment #MLOps #DevOps #LargeLanguageModels #InferenceEngine #Ollama #OCIArtifacts #CUDA #PyTorch #DependencyHell #AITutorial #MachineLearning