Update README.md

README.md

@@ -15,17 +15,17 @@ The dataset is fully open for research and educational purposes. Use of the data
 
 
 ## How to download dataset:
-Everything that is related directly to the dataset is located within this repo. For instructions related to testing the model used or verifying results from TACDEC-paper, see [TACDEC-model](https://huggingface.co/SimulaMet-HOST/TACDEC-model) repo.
+Everything that is related directly to the dataset is located within this repo. For instructions related to testing the model used or verifying results from TACDEC-paper, see [TACDEC-model repo](https://huggingface.co/SimulaMet-HOST/TACDEC-model).
 
 What you can find in this repo is:
 - All 425 [videos](https://huggingface.co/datasets/SimulaMet-HOST/TACDEC/resolve/main/videos.zip)
 - All 425 [labels](https://huggingface.co/datasets/SimulaMet-HOST/TACDEC/resolve/main/labels.zip)
 
 In addition:
-- A torch, [sorted_cls_tokens_feature.pt](https://huggingface.co/datasets/SimulaMet-HOST/TACDEC/resolve/main/sorted_cls_tokens_features.pt) , containing all the CLS-tokens (features) from DINOv2 used concatenated in a sorted order
+- A torch, [sorted_cls_tokens_feature.pt](https://huggingface.co/datasets/SimulaMet-HOST/TACDEC/resolve/main/sorted_cls_tokens_features.pt), containing all the CLS-tokens (features) from DINOv2 used concatenated in a sorted order
 - A numpy array, [sorted_cls_tokens_labels.npy](https://huggingface.co/datasets/SimulaMet-HOST/TACDEC/resolve/main/sorted_cls_tokens_labels.npy), containing all the labels used, concatenated in the same sorted order 
 
-We highly recommend downloading these if you choose to implement/test the model, as running the large DINOv2 model is highly computationally expensive. 
+We highly recommend downloading these if you want to implement/test the model, as running the large DINOv2 model is highly computationally expensive. 
 
 
 **Citation:**
@@ -47,7 +47,7 @@ We highly recommend downloading these if you choose to implement/test the model,
 
 **Contact**
 
-For any questions regarding the dataset, or to discuss potential collaboration and joint research opportunities, please contact the following people:
+For any questions regarding the dataset, or to discuss potential collaboration and joint research opportunities, please get in touch with the following people:
 
 - Evan Jåsund Kassab: evanjk@uio.no
 - Cise Midoglu: cise@simula.no