Update README.md

README.md

@@ -54,7 +54,7 @@ ds = datasets.load_dataset("Zyphra/dclm-dedup", split="train")
 
 We deduplicated DCLM using the approximate minhash LSH method implemented in NeMo Curator with the following parameters: minhash with signature size of 128 computed on character-based 25-grams signatures and split into 8 bands, giving roughly 85% Jaccard similarity threshold. We then constructed an undirected graph with nodes being documents and edges being duplicates, and found connected components in it, which provided us with clusters of duplicates. From each cluster, we selected a random document to keep and removed the rest. 
 
-The deduplication process is closely related to how we created our [Zyda-2](https://huggingface.co/datasets/Zyphra/Zyda-2) dataset, for which we released full reproduction [tutorial](https://github.com/NVIDIA/NeMo-Curator/tree/main/tutorials/zyda2-tutorial). Instead of doing careful cross-deduplication between components of Zyda-2, we only focused on DCLM itself, aggressively removing duplicated documents.
+The deduplication process is closely related to how we created our [Zyda-2](https://huggingface.co/datasets/Zyphra/Zyda-2) dataset, for which we released full reproduction [tutorial](https://github.com/NVIDIA/NeMo-Curator/tree/main/tutorials/zyda2-tutorial). Instead of doing careful cross-deduplication between components of Zyda-2, we only focused on DCLM itself for this release, aggressively removing duplicated documents.
 
 ### Dataset Description