Remove legacy models in the readmes.

Update nlp/README.md according to the update in vision/.

PiperOrigin-RevId: 442428156

official/README.md

@@ -38,16 +38,15 @@ In the near future, we will add:
 
 ## Models and Implementations
 
-### Computer Vision
+### [Computer Vision](vision/README.md)
 
 #### Image Classification
 
 | Model | Reference (Paper) |
 |-------|-------------------|
-| [MNIST](legacy/image_classification) | A basic model to classify digits from the [MNIST dataset](http://yann.lecun.com/exdb/mnist/) |
 | [ResNet](vision/MODEL_GARDEN.md) | [Deep Residual Learning for Image Recognition](https://arxiv.org/abs/1512.03385) |
 | [ResNet-RS](vision/MODEL_GARDEN.md) | [Revisiting ResNets: Improved Training and Scaling Strategies](https://arxiv.org/abs/2103.07579) |
-| [EfficientNet](legacy/image_classification) | [EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks](https://arxiv.org/abs/1905.11946) |
+| [EfficientNet](vision/MODEL_GARDEN.md) | [EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks](https://arxiv.org/abs/1905.11946) |
 | [Vision Transformer](vision/MODEL_GARDEN.md) | [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://arxiv.org/abs/2010.11929) |
 
 #### Object Detection and Segmentation
@@ -56,7 +55,6 @@ In the near future, we will add:
 |-------|-------------------|
 | [RetinaNet](vision/MODEL_GARDEN.md) | [Focal Loss for Dense Object Detection](https://arxiv.org/abs/1708.02002) |
 | [Mask R-CNN](vision/MODEL_GARDEN.md) | [Mask R-CNN](https://arxiv.org/abs/1703.06870) |
-| [ShapeMask](legacy/detection) | [ShapeMask: Learning to Segment Novel Objects by Refining Shape Priors](https://arxiv.org/abs/1904.03239) |
 | [SpineNet](vision/MODEL_GARDEN.md) | [SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization](https://arxiv.org/abs/1912.05027) |
 | [Cascade RCNN-RS and RetinaNet-RS](vision/MODEL_GARDEN.md) | [Simple Training Strategies and Model Scaling for Object Detection](https://arxiv.org/abs/2107.00057)|
 
@@ -66,7 +64,7 @@ In the near future, we will add:
 |-------|-------------------|
 | [Mobile Video Networks (MoViNets)](projects/movinet) | [MoViNets: Mobile Video Networks for Efficient Video Recognition](https://arxiv.org/abs/2103.11511) |
 
-### Natural Language Processing
+### [Natural Language Processing](nlp/README.md)
 
 | Model | Reference (Paper) |
 |-------|-------------------|
@@ -74,7 +72,6 @@ In the near future, we will add:
 | [BERT (Bidirectional Encoder Representations from Transformers)](nlp/MODEL_GARDEN.md#available-model-configs) | [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://arxiv.org/abs/1810.04805) |
 | [NHNet (News Headline generation model)](projects/nhnet) | [Generating Representative Headlines for News Stories](https://arxiv.org/abs/2001.09386) |
 | [Transformer](nlp/MODEL_GARDEN.md#available-model-configs) | [Attention Is All You Need](https://arxiv.org/abs/1706.03762) |
-| [XLNet](nlp/xlnet) | [XLNet: Generalized Autoregressive Pretraining for Language Understanding](https://arxiv.org/abs/1906.08237) |
 | [MobileBERT](projects/mobilebert) | [MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices](https://arxiv.org/abs/2004.02984) |
 
 ### Recommendation

official/nlp/README.md

-# TensorFlow NLP Modelling Toolkit
+# TF-NLP Model Garden
+
+⚠️ Disclaimer: All datasets hyperlinked from this page are not owned or
+distributed by Google. The dataset is made available by third parties.
+Please review the terms and conditions made available by the third parties
+before using the data.
 
 This codebase provides a Natrual Language Processing modeling toolkit written in
 [TF2](https://www.tensorflow.org/guide/effective_tf2). It allows researchers and