Open-Source Model Ops: Self-Hosting, Fine-Tuning and Governance with Devstral & Mistral Models Training Course

Introduction to Devstral and Mistral Models

• Overview of Mistral’s open-source model offerings.
• Apache-2.0 licensing and its role in enterprise adoption.
• The contribution of Devstral to coding and agentic workflows.

Self-Hosting Mistral and Devstral Models

• Preparing environments and selecting infrastructure.
• Containerization and deployment using Docker and Kubernetes.
• Addressing scaling requirements for production use.

Fine-Tuning Techniques

• Comparing supervised fine-tuning with parameter-efficient tuning.
• Dataset preparation and cleaning processes.
• Illustrative examples of domain-specific customization.

Model Ops and Versioning

• Best practices for managing the model lifecycle.
• Strategies for model versioning and rollback.
• Integrating CI/CD pipelines for ML models.

Governance and Compliance

• Security implications of open-source deployment.
• Ensuring monitoring and auditability in enterprise contexts.
• Adhering to compliance frameworks and responsible AI practices.

Monitoring and Observability

• Tracking model drift and accuracy degradation.
• Instrumenting for optimal inference performance.
• Defining alerting and response workflows.

Case Studies and Best Practices

• Industry case studies on Mistral and Devstral adoption.
• Striking a balance between cost, performance, and control.
• Key lessons derived from open-source Model Ops.

Summary and Next Steps