1. Introduction
  3. Core Concepts
  4. What is Pacha?
  5. MLOps Artifact Management
  6. Semantic Versioning for ML
  7. Reproducibility Principles
  9. Architecture
  10. System Overview
  11. Content-Addressed Storage
  12. SQLite Metadata Store
  13. BLAKE3 Hashing
  15. Model Registry
  16. Model Versioning
  17. Model Cards
  18. Lifecycle Stages
  19. Model Lineage
  21. Data Registry
  22. Dataset Versioning
  23. Datasheets
  24. Data Provenance
  26. Recipe Registry
  27. Training Recipes
  28. Hyperparameters
  29. Environment Dependencies
  31. Storage Layer
  32. Content Addressing
  33. Deduplication
  34. Integrity Verification
  35. Compression
  37. Lineage Tracking
  38. Lineage Graph
  39. Model Derivation
  40. Fine-Tuning Lineage
  41. Quantization Tracking
  43. CLI Reference
  44. Installation
  45. Model Commands
  46. Data Commands
  47. Recipe Commands
  48. Run Commands
  50. Examples
  51. Quick Start
  52. Registering Models
  53. Tracking Experiments
  54. Managing Datasets
  55. Training Workflows
  57. Best Practices
  58. Versioning Strategy
  59. Model Documentation
  60. Reproducibility Checklist
  61. CI/CD Integration
  63. Appendix
  64. Glossary
  65. References
  66. API Reference