docs: Sync docs from Google repo (#10402)

Author: kevinthecheung

docs/app-check/default-providers.md

@@ -18,7 +18,7 @@ only your app can access your project's Firebase resources. See an
     already done so.
 
 1.  Register your apps to use App Check with the Play Integrity, Device Check, and reCAPTCHA providers in the
-    [**Project Settings > App Check**](https://console.firebase.google.com/project/_/settings/appcheck)
+    [**Project Settings > App Check**](https://console.firebase.google.com/project/_/appcheck)
     section of the Firebase console.
 
     You usually need to register all of your project's apps, because once you

docs/ml/use-custom-models.md

@@ -20,6 +20,10 @@ devices. To get a TensorFlow Lite model:
 - Use a pre-built model, such as one of the [official TensorFlow Lite models](https://www.tensorflow.org/lite/models){:.external}
 - [Convert a TensorFlow model, Keras model, or concrete function to TensorFlow Lite.](https://www.tensorflow.org/lite/convert){:.external}
 
+Note that in the absence of a maintained TensorFlow Lite library for Dart, you
+will need to integrate with the native TensorFlow Lite library for your
+platforms. This integration is not documented here.
+
 ## Before you begin
 
 1.  [Install and initialize the Firebase SDKs for Flutter](/docs/flutter/setup)
@@ -120,14 +124,10 @@ so at any point before you need to use the model.
 ## 3. Perform inference on input data
 
 Now that you have your model file on the device you can use it with the
-TensorFlow Lite interpreter to perform inference. For this, you have several
-options:
-
-- The [native TensorFlow Lite libraries](https://www.tensorflow.org/lite){:.external}
-  for iOS and Android.
-- One of the community-developed Flutter plugins, such as
-  [`tflite_flutter`](https://pub.dev/packages/tflite_flutter){:.external} or
-  [`tflite`](https://pub.dev/packages/tflite){:.external}.
+TensorFlow Lite interpreter to perform inference. In the absence of a maintained
+TensorFlow Lite library for Dart, you will need to integrate with the
+[native TensorFlow Lite libraries](https://www.tensorflow.org/lite){:.external}
+for iOS and Android.
 
 
 ## Appendix: Model security {:#model_security}