docs: added model versioning documentation

[vsraccubits]

Issue Title: Feature: Added Model Versioning

Description

• Feature Description: Introduced support for model versioning within the system. This feature allows users to create, manage, and track different versions of a model. Each version can have its own metadata, deployment status, and configuration settings.

• Use Case: Model versioning is essential for managing the lifecycle of ML models. It enables users to update models without losing previous versions, roll back to stable versions if issues arise, and compare performance across versions for auditing and improvement purposes.

Expected Behavior

- Users should be able to create new versions of an existing model.
- Each version should retain its own unique metadata and settings.
- The system should clearly display and differentiate between model versions.
- Existing integrations and workflows should continue to function without disruption.