Update README.md

README.md

@@ -6,18 +6,28 @@ TACDEC is a dataset of tackle events in soccer game videos. Recognizing the gap
 
 
 **Zenodo**
-
 The dataset is also available on Zenodo: https://zenodo.org/records/10611979.
 
-**Additional Resources**
-
-Additional resources related to TACDEC can be found under: https://github.com/simula/TACDEC/.
 
 ## Terms of Use
 
 The dataset is fully open for research and educational purposes. Use of the dataset for competitions or commercial purposes requires prior written permission. References to the related article must be included in all documents and papers that use, refer to, or report experimental results from this dataset.
 
 
+## 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.
+
+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 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. 
+
+
 **Citation:**
 <pre><code>
 @incollection{Kassab_MMSYS_ODS,