Improve dataset card: Add tags and prominent paper/code links

This PR enhances the dataset card by:
- Adding relevant `tags` (`semi-supervised-learning`, `deduplicated`, `stl-10`) and the `language` tag to the metadata for improved discoverability.
- Adding prominent links to the associated paper ([SemiOccam: A Robust Semi-Supervised Image Recognition Network Using Sparse Labels](https://huggingface.co/papers/2506.03582)) and its official code repository ([https://github.com/Shu1L0n9/SemiOccam](https://github.com/Shu1L0n9/SemiOccam)) directly below the main title for immediate access.

README.md

@@ -3,6 +3,12 @@ license: apache-2.0
 task_categories:
 - image-classification
 library_name: datasets
+language:
+- en
+tags:
+- semi-supervised-learning
+- deduplicated
+- stl-10
 configs:
 - config_name: default
   data_files:
@@ -16,6 +22,8 @@ configs:
 
 # Dataset Card for STL-10 Cleaned (Deduplicated Training Set)
 
+[Paper](https://huggingface.co/papers/2506.03582) | [Code](https://github.com/Shu1L0n9/SemiOccam)
+
 ## Dataset Description
 
 This dataset is a modified version of the [STL-10 dataset](https://cs.stanford.edu/~acoates/stl10/). The primary modification involves **deduplicating the training set** by removing any images that are exact byte-for-byte matches (based on SHA256 hash) with images present in the original STL-10 test set. The dataset comprises this cleaned training set and the original, unmodified STL-10 test set.