TechniquesAdvanced

MLOps for LLMs

Build production MLOps pipelines for fine-tuning and deploying LLMs

4-8 weeks
2-5 people
6 tools
Key Tools
Weights & BiasesMLflowDVCHugging FaceModalReplicate
Implementation Steps
  1. 1

    Set up data versioning with DVC

  2. 2

    Implement experiment tracking with W&B

  3. 3

    Create fine-tuning pipelines on Modal

  4. 4

    Register models in MLflow or HuggingFace Hub

  5. 5

    Set up model evaluation before deployment

  6. 6

    Implement blue-green deployment for models

  7. 7

    Add monitoring for model drift

Expected Outcomes
  • Reproducible training pipelines
  • Versioned datasets and models
  • Automated model deployment
  • Production model monitoring
Pro Tips
  • Start with small models for pipeline testing
  • Version everything - code, data, configs
  • Automate evaluation gates
  • Plan for rollback scenarios
All PlaybooksExplore Tools