Internal change

PiperOrigin-RevId: 487075916

official/nlp/README.md

@@ -64,3 +64,8 @@ details.
 We provide a large collection of baselines and checkpoints for NLP pre-trained
 models. Please see [docs/pretrained_models.md](docs/pretrained_models.md) for
 more details.
+
+## More Documentations
+
+Please read through the model training tutorials and references in the
+[docs/ folder](docs/README.md).

official/vision/README.md

@@ -293,3 +293,8 @@ training features including:
 | MoViNet-A4-Base | 80 x 3            | 83.48 | 96.16 | [config](https://github.com/tensorflow/models/blob/master/official/projects/movinet/configs/yaml/movinet_a4_k600_8x8.yaml) |
 | MoViNet-A5-Base | 120 x 2           | 84.27 | 96.39 | [config](https://github.com/tensorflow/models/blob/master/official/projects/movinet/configs/yaml/movinet_a5_k600_8x8.yaml) |
 </details>
+
+## More Documentations
+
+Please read through the references in the
+[examples/starter](examples/starter).

official/vision/examples/starter/README.md

@@ -166,10 +166,10 @@ You can see in this file we import all our custom components:
 ```python
 # pylint: disable=unused-import
 from official.common import registry_imports
-from official.vision.beta.projects.example import example_config
-from official.vision.beta.projects.example import example_input
-from official.vision.beta.projects.example import example_model
-from official.vision.beta.projects.example import example_task
+from official.vision.examples.starter import example_config
+from official.vision.examples.starter import example_input
+from official.vision.examples.starter import example_model
+from official.vision.examples.starter import example_task
 ```
 
 ## Training
@@ -179,14 +179,14 @@ You can create your own trainer by branching from our core
 Just make sure you import the registry like this:
 
 ```python
-from official.vision.beta.projects.example import registry_imports  # pylint: disable=unused-import
+from official.vision.examples.starter import registry_imports  # pylint: disable=unused-import
 ```
 
 You can run training locally for testing purpose:
 
 ```bash
-# Assume you are under official/vision/projects.
-python3 example/train.py \
+# Assume you are under official/vision/examples.
+python3 starter/train.py \
   --experiment=tf_vision_example_experiment \
   --config_file=${PWD}/example/example_config_local.yaml \
   --mode=train \