Add pipeline tag

This PR improves the model card by adding the `pipeline_tag: image-feature-extraction` to the metadata. This will help users discover the model when filtering by pipeline type on the Hugging Face Hub and understand its primary functionality.

README.md

@@ -1,9 +1,11 @@
 ---
-library_name: transformers
-license: apache-2.0
 datasets:
 - ILSVRC/imagenet-1k
+library_name: transformers
+license: apache-2.0
+pipeline_tag: image-feature-extraction
 ---
+
 # NEPA: Next-Embedding Prediction Makes Strong Vision Learners
 
 [![Paper](https://img.shields.io/badge/arXiv-Paper-b31b1b?logo=arxiv&logoColor=b31b1b)](https://arxiv.org/abs/2512.16922)
@@ -197,7 +199,7 @@ python init_nepa_cls_from_pretrain.py \
 
 ## Acknowledgements
 
-We gratefully acknowledge the developers of [Transformers](https://github.com/huggingface/transformers), [Evaluate](https://github.com/huggingface/evaluate), and [timm](https://github.com/huggingface/pytorch-image-models) for their excellent open-source contributions.
+We gratefully acknowledge the developers of [Transformers](https://github.com/huggingface/transformers), [Datasets](https://github.com/huggingface/datasets), [Evaluate](https://github.com/huggingface/evaluate), and [timm](https://github.com/huggingface/pytorch-image-models) for their excellent open-source contributions.
 
 ## Contact