Improve dataset card with task category and Github link

README.md

@@ -1,6 +1,13 @@
 ---
 license: mit
+task_categories:
+- text-generation
+tags:
+- data-selection
+- pretraining
+- efficient-training
 ---
+
 <p align="center">
     📑 <a href="https://arxiv.org/abs/2503.00808" target="_blank">Paper</a> &nbsp&nbsp | &nbsp&nbsp 🔨 <a href="https://huggingface.co/hkust-nlp/preselect-fasttext-classifier" target="_blank">fastText Classifier</a> &nbsp&nbsp | &nbsp&nbsp 🤗 <a href="https://huggingface.co/datasets/hkust-nlp/PreSelect-100B" target="_blank">Released Dataset</a> &nbsp&nbsp | &nbsp&nbsp 📦 <a href="https://github.com/hkust-nlp/PreSelect" target="_blank">Repo</a>  
 <br>
@@ -10,7 +17,7 @@ PreSelect-100B is a curated ~100B token pretraining dataset that achieves great
 It is filtered by [PreSelect-Classifier](https://huggingface.co/hkust-nlp/PreSelect-classifier) at 10% threshold, where the pool is a randomly sampled subset of [DCLM-refinedweb](https://data.commoncrawl.org/contrib/datacomp/DCLM-refinedweb/index.html), which is a cleaned version of Common Crawl raw data but without any model-based filtering.
 
 ### Benchmark results
-Trianing using PreSelect curated dataset achieve superior results than other dataset selection methods on various downstream tasks and below are comparisons.
+Training using the PreSelect curated dataset achieves superior results than other dataset selection methods on various downstream tasks, as shown in the comparison below.
 
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/641c9662043963b1c0a1df52/_2eDuE5K06giMepA_lNSp.png)
 
@@ -24,6 +31,4 @@ If you find this work helpful, please kindly cite as:
       year={2025},
       eprint={2503.00808},
 }
-```
-
-
+```