update mlflow plugin

Author: Adam-D-Lewis

docs/community/plugins.md

@@ -12,6 +12,6 @@ You can learn to use and create Nebari extensions in the [extension mechanism do
 
 The following community-developed extensions are recognized and verified by the Nebari development team.
 
-- The **[ML Flow extension for AWS](https://github.com/MetroStar/nebari-mlflow-aws)** is designed to integrate [MLFlow](https://mlflow.org/) into Nebari deployments utilizing AWS (Amazon Web Services) as the provider. It provides a robust, collaborative environment for AI/ML professionals to manage experiments, track metrics, and deploy models.
+- The **[Nebari MLFlow Plugin](https://github.com/nebari-dev/nebari-mlflow-plugin)** is designed to integrate [MLFlow](https://mlflow.org/) into Nebari deployments. It currently supports Azure and GCP providers, with AWS support planned for the future. It provides a robust, collaborative environment for AI/ML professionals to manage experiments, track metrics, and deploy models.
 - The **[Label Studio](https://github.com/MetroStar/nebari-label-studio)** integrates [Label Studio](https://labelstud.io/) into the Nebari platform, allowing seamless labeling functionality within Nebari. Utilizing Python, Terraform, Kubernetes, and Helm charts, the plugin provides a configurable deployment and authentication through Keycloak.
 - The **[Self Registration](https://github.com/nebari-dev/nebari-self-registration)** extension allows potential new users of a Nebari deployment to self-register through a coupon code. A new self-registration page is generated on the Nebari server where users can input their information and a coupon code. Once the form is validated, the new user will be auto-generated on the Nebari deployment. It can also be configured to give new users a set expiration date.