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SimulaMet-HOST
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TACDEC

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Evanjaa commited on Mar 25

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@@ -22,8 +22,8 @@ What you can find in this repo is:
 - 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.

 - 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.