Docs Prettier reformat (#13483)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

docs/en/integrations/mlflow.md

@@ -68,7 +68,7 @@ Make sure that MLflow logging is enabled in Ultralytics settings. Usually, this
     export MLFLOW_EXPERIMENT_NAME=<your_experiment_name>
     ```
 
-   Or use the `project=<project>` argument when training a YOLO model, i.e. `yolo train project=my_project`.
+    Or use the `project=<project>` argument when training a YOLO model, i.e. `yolo train project=my_project`.
 
 2. **Set a Run Name**: Similar to setting a project name, you can set the run name via an environment variable:
 
@@ -76,7 +76,7 @@ Make sure that MLflow logging is enabled in Ultralytics settings. Usually, this
     export MLFLOW_RUN=<your_run_name>
     ```
 
-   Or use the `name=<name>` argument when training a YOLO model, i.e. `yolo train project=my_project name=my_name`.
+    Or use the `name=<name>` argument when training a YOLO model, i.e. `yolo train project=my_project name=my_name`.
 
 3. **Start Local MLflow Server**: To start tracking, use:
 
@@ -84,7 +84,7 @@ Make sure that MLflow logging is enabled in Ultralytics settings. Usually, this
     mlflow server --backend-store-uri runs/mlflow'
     ```
 
-   This will start a local server at http://127.0.0.1:5000 by default and save all mlflow logs to the 'runs/mlflow' directory. To specify a different URI, set the `MLFLOW_TRACKING_URI` environment variable.
+    This will start a local server at http://127.0.0.1:5000 by default and save all mlflow logs to the 'runs/mlflow' directory. To specify a different URI, set the `MLFLOW_TRACKING_URI` environment variable.
 
 4. **Kill MLflow Server Instances**: To stop all running MLflow instances, run: