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--- a/infra/website/docs/blog/feast-mlflow-native-integration.md
+++ b/infra/website/docs/blog/feast-mlflow-native-integration.md
@@ -5,8 +5,8 @@ date: 2026-06-01
authors: ["Vanshika"]
---
-
-

+
+
# Native MLflow Integration for Feast
@@ -259,13 +259,10 @@ pip install feast[mlflow]
Add the `mlflow:` block to your `feature_store.yaml`, start an MLflow tracking server, and run your training code. Features are automatically linked to experiments from the first retrieval.
-For a complete end-to-end walkthrough — from feature definition through model training, registration, and feature resolution — see the [demo notebook](https://github.com/feast-dev/feast/tree/master/examples/mlflow).
-
-
## Join the Conversation
We'd love to hear how you're using (or plan to use) the Feast–MLflow integration. Reach out on [Slack](https://slack.feast.dev/) or [GitHub](https://github.com/feast-dev/feast) — issues and PRs welcome!
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