diff --git a/README.md b/README.md
index 3b3aadb..6ed492b 100644
--- a/README.md
+++ b/README.md
@@ -6,27 +6,27 @@ Discover pretrained models for deep learning in MATLAB.
 
 ### Computer Vision
 * [Image Classification](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#image-classification-)
-* [Object Detection](#ObjectDetection)
-* [Semantic Segmentation](#SemanticSegmentation)
-* [Instance Segmentation](#InstanceSegmentation)
-* [Image Translation](#ImageTranslation)
-* [Pose Estimation](#PoseEstimation)
-* [Video Classification](#VideoClassification)
-* [Text Detection & Recognition](#textdetection)
+* [Object Detection](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#object-detection-)
+* [Semantic Segmentation](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#semantic-segmentation-)
+* [Instance Segmentation](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#instance-segmentation-)
+* [Image Translation](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#image-translation-)
+* [Pose Estimation](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#pose-estimation-)
+* [Video Classification](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#video-classification-)
+* [Text Detection & Recognition](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#text-detection-and-recognition-)
 
 ### Natural Language Processing
-* [Transformers](#transformers)
+* [Transformers](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#transformers-text-)
 
 ### Audio
-* [Audio Embeddings](#AudioEmbeddings)
+* [Audio Embeddings](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#audio-embeddings-)
 * [Sound Classification](#SoundClassification)
 * [Pitch Estimation](#PitchEstimation)
-* [Speech to Text](#Speech2Text)
+* [Speech to Text](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#speech-to-text-)
 
 ### Lidar 
-* [Point Cloud Classification](#PointCloud)
-* [Point Cloud Segmentation](#PointCloudSeg)
-* [Point Cloud Object Detection](#PointCloudObj)
+* [Point Cloud Classification](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#lidar-)
+* [Point Cloud Segmentation](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#lidar-)
+* [Point Cloud Object Detection](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#lidar-)
 
 ## Image Classification <a name="ImageClassification"/>
 
@@ -70,7 +70,7 @@ Pretrained networks have different characteristics that matter when choosing a n
 ![](Images/pretrained.png)
 Figure. Comparing image classification model accuracy, speed and size.
 
-[Back to top](#Models)
+[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)
 
 ## Object Detection <a name="ObjectDetection"/>
 
@@ -104,7 +104,7 @@ These networks have been trained to detect specific objects for a given applicat
 | [Single Shot Detector (SSD)](https://www.mathworks.com/help/vision/ug/object-detection-using-single-shot-detector.html)   | Vehicle detection | 44 |[Doc ](https://www.mathworks.com/help/vision/ug/object-detection-using-single-shot-detector.html)|<img src="Images/ObjectDetectionUsingSSD.png" width=150>|
 | [Faster R-CNN](https://www.mathworks.com/help/vision/ug/object-detection-using-faster-r-cnn-deep-learning.html)   | Vehicle detection | 118 |[Doc](https://www.mathworks.com/help/vision/ug/object-detection-using-faster-r-cnn-deep-learning.html)|<img src="Images/faster_rcnn.png" width=150>|
 
-[Back to top](#Models)
+[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)
 
 ## Semantic Segmentation <a name="SemanticSegmentation"/>
 
@@ -127,7 +127,7 @@ This network has been trained to detect 20 objects classes from the PASCAL VOC d
 | [AdaptSeg (GAN)](https://www.mathworks.com/help/deeplearning/ug/train-deep-learning-semantic-segmentation-network-using-3d-simulation-data.html)  | Model tuning using 3-D simulation data | 54.4 | [Doc](https://www.mathworks.com/help/deeplearning/ug/train-deep-learning-semantic-segmentation-network-using-3d-simulation-data.html) |<img src="Images/adaptSeg.png" width=150>|
 
 
-[Back to top](#Models)
+[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)
 
 ## Instance Segmentation <a name="InstanceSegmentation"/>
 
@@ -141,7 +141,7 @@ Inputs are RGB images, outputs are pixel classifications (semantic maps), boundi
 | ------------- | ------------- |------------- |
 | [Mask R-CNN](https://www.mathworks.com/help/vision/ref/maskrcnn.html) | 80 | [Doc](https://www.mathworks.com/help/vision/ref/maskrcnn.html) <br />  [Github](https://github.com/matlab-deep-learning/mask-rcnn)|
 
-[Back to top](#Models)
+[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)
 
 ## Image Translation <a name="ImageTranslation"/>
 
@@ -159,7 +159,7 @@ Inputs are images, outputs are translated RGB images. This example workflow show
 | [CycleGAN](https://www.mathworks.com/help/images/unsupervised-medical-image-denoising-using-cyclegan.html) | Medical Image Denoising | 75.3 | [Doc](https://www.mathworks.com/help/images/unsupervised-medical-image-denoising-using-cyclegan.html) |<img src="Images/cyclegan_imagedenoising.png" width=150>|
 | [VDSR](https://www.mathworks.com/help/images/single-image-super-resolution-using-deep-learning.html) | Super Resolution (estimate a high-resolution image from a low-resolution image) | 2.4 | [Doc](https://www.mathworks.com/help/images/single-image-super-resolution-using-deep-learning.html) |<img src="Images/SuperResolution.png" width=150>|
 
-[Back to top](#Models)
+[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)
 
 ## Pose Estimation <a name="PoseEstimation"/>
 
@@ -173,7 +173,7 @@ All inputs are RGB images, outputs are heatmaps and part affinity fields (PAFs)
 | ------------- | ------------- |------------- |
 | [OpenPose](https://www.mathworks.com/help/deeplearning/ug/estimate-body-pose-using-deep-learning.html)   | 14 | [Doc](https://www.mathworks.com/help/deeplearning/ug/estimate-body-pose-using-deep-learning.html) |
 
-[Back to top](#Models)
+[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)
 
 ## Video Classification <a name="VideoClassification"/>
 
@@ -189,7 +189,7 @@ All inputs are Videos only or Video with Optical Flow data, outputs are gesture
 | [R(2+1)D](https://www.mathworks.com/help/vision/ref/r2plus1dvideoclassifier.html) | Video | 112 |400 |Faster convergence than Inflated-3D|[Doc](https://www.mathworks.com/help/vision/ref/r2plus1dvideoclassifier.html)
 | [Inflated-3D](https://www.mathworks.com/help/vision/ref/inflated3dvideoclassifier.html) | Video & Optical Flow data | 91 | 400 |Accuracy of the classifier improves when combining optical flow and RGB data.| [Doc](https://www.mathworks.com/help/vision/ref/inflated3dvideoclassifier.html)
 
-[Back to top](#Models)
+[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)
 
 ## Text Detection and Recognition <a name="textdetection"/>
 
@@ -209,7 +209,7 @@ Inputs are RGB images, outputs are bounding boxes that identify regions of text.
 | ------------- | ------------- |------------- |------------- |------------- |
 | [Seven Segment Digit Recognition](https://github.com/matlab-deep-learning/Seven-Segment-Digit-Recognition)   |Seven segment digit recognition using deep learning and OCR. This is helpful in industrial automation applications where digital displays are often surrounded with complex background. | 3.8 |[GitHub](https://github.com/matlab-deep-learning/Seven-Segment-Digit-Recognition)  |![](Images/7segment.png)|
 
-[Back to top](#Models)
+[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)
 
 ## Transformers (Text) <a name="transformers"/>
 
@@ -231,7 +231,7 @@ Inputs are sequences of text, outputs are text feature embeddings.
 | [FinBERT](https://github.com/matlab-deep-learning/transformer-models#bert-and-finbert)   | The FinBERT model is a BERT model for financial sentiment analysis | 388 |[GitHub](https://github.com/matlab-deep-learning/transformer-models#bert-and-finbert) |![](Images/finbert.png)|
 | [GPT-2](https://github.com/matlab-deep-learning/transformer-models#gpt-2) | The GPT-2 model is a decoder model used for text summarization.| 1.2GB |[GitHub](https://github.com/matlab-deep-learning/transformer-models#gpt-2) |![](Images/gpt2.png)|
 
-[Back to top](#Models)
+[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)
 
 ## Audio Embeddings <a name="AudioEmbeddings"/>
 
@@ -267,7 +267,7 @@ Inputs are Audio signals, outputs is text.
 | [wav2vec](https://github.com/matlab-deep-learning/wav2vec-2.0)   | Speech to Text | 236| 3.2 |[GitHub](https://github.com/matlab-deep-learning/wav2vec-2.0) |
 | [deepspeech](https://github.com/matlab-deep-learning/deepspeech)   | Speech to Text | 167| 5.97 |[GitHub](https://github.com/matlab-deep-learning/deepspeech) |
 
-[Back to top](#Models)
+[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)
 
 ## Lidar <a name="PointCloud"/>
 
@@ -287,7 +287,7 @@ Inputs are Lidar Point Clouds converted to five-channels, outputs are segmentati
 | <a name="PointCloudObj"/>[PointPillars](https://www.mathworks.com/help/lidar/ug/object-detection-using-pointpillars-network.html)   | Object Detection | 8| 3 |[Doc](https://www.mathworks.com/help/lidar/ug/object-detection-using-pointpillars-network.html)|
 | [Complex YOLO v4](https://github.com/matlab-deep-learning/Lidar-object-detection-using-complex-yolov4)   | Object Detection | 233 (complex-yolov4) <br /> 21 (tiny-complex-yolov4) | 3 |[GitHub](https://github.com/matlab-deep-learning/Lidar-object-detection-using-complex-yolov4)|
 
-[Back to top](#Models)
+[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)
 
 ## Model requests
 If you'd like to request MATLAB support for additional pretrained models, [**please create an issue from this repo**](https://docs.github.com/en/issues/tracking-your-work-with-issues/creating-an-issue).