GitBook: [#4] Backport fix for odfv flag error

docs/reference/alpha-on-demand-feature-view.md

@@ -1,14 +1,14 @@
-# \[Alpha\] On demand feature view
+# \[Alpha] On demand feature view
 
 **Warning**: This is an _experimental_ feature. It's intended for early testing and feedback, and could change without warnings in future releases.
 
 {% hint style="info" %}
-To enable this feature, run **`feast alpha enable enable_on_demand_transforms`**
+To enable this feature, run **`feast alpha enable on_demand_transforms`**
 {% endhint %}
 
 ## Overview
 
-On demand feature views allows users to use existing features and request time data \(features only available at request time\) to transform and create new features. Users define python transformation logic which is executed in both historical retrieval and online retrieval paths.
+On demand feature views allows users to use existing features and request time data (features only available at request time) to transform and create new features. Users define python transformation logic which is executed in both historical retrieval and online retrieval paths.
 
 Currently, these transformations are executed locally. Future milestones include building a Feature Transformation Server for executing transformations at higher scale.
 
@@ -17,11 +17,11 @@ Currently, these transformations are executed locally. Future milestones include
 There are new CLI commands:
 
 * `feast on-demand-feature-views list` lists all registered on demand feature view after `feast apply` is run
-* `feast on-demand-feature-views describe [NAME]`  describes the definition of an on demand feature view
+* `feast on-demand-feature-views describe [NAME]` describes the definition of an on demand feature view
 
 ## Example
 
-See [https://github.com/feast-dev/on-demand-feature-views-demo](https://github.com/feast-dev/on-demand-feature-views-demo) for an example on how to use on demand feature views. 
+See [https://github.com/feast-dev/on-demand-feature-views-demo](https://github.com/feast-dev/on-demand-feature-views-demo) for an example on how to use on demand feature views.
 
 ### **Registering transformations**
 
@@ -59,7 +59,7 @@ def transformed_conv_rate(features_df: pd.DataFrame) -> pd.DataFrame:
 ### **Feature retrieval**
 
 {% hint style="info" %}
-The on demand feature view's name is the function name \(i.e. `transformed_conv_rate`\). 
+The on demand feature view's name is the function name (i.e. `transformed_conv_rate`).
 {% endhint %}
 
 And then to retrieve historical or online features, we can call this in a feature service or reference individual features:
@@ -76,4 +76,3 @@ training_df = store.get_historical_features(
     ],
 ).to_df()
 ```
-