Deploying and Optimizing LLMs with Ollama Training Course

Introduction to Ollama for LLM Deployment

• Overview of Ollama’s capabilities
• Advantages of local AI model deployment for government operations
• Comparison with cloud-based AI hosting solutions for government use

Setting Up the Deployment Environment

• Installing Ollama and required dependencies for government systems
• Configuring hardware and GPU acceleration to support government applications
• Dockerizing Ollama for scalable deployments in government environments

Deploying LLMs with Ollama

• Loading and managing AI models for government use
• Deploying Llama 3, DeepSeek, Mistral, and other models for government applications
• Creating APIs and endpoints for secure AI model access in government systems

Optimizing LLM Performance

• Fine-tuning models for efficiency in government operations
• Reducing latency and improving response times for government services
• Managing memory and resource allocation to enhance performance in government settings

Integrating Ollama into AI Workflows

• Connecting Ollama to applications and services for government use
• Automating AI-driven processes to improve government efficiency
• Using Ollama in edge computing environments for government operations

Monitoring and Maintenance

• Tracking performance and debugging issues in government deployments
• Updating and managing AI models to ensure reliability in government systems
• Ensuring security and compliance in AI deployments for government use

Scaling AI Model Deployments

• Best practices for handling high workloads in government operations
• Scaling Ollama for enterprise use cases in government agencies
• Future advancements in local AI model deployment for government applications

Summary and Next Steps