? 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