Update README.md

README.md

@@ -44,11 +44,10 @@ According to our evaluations, Zyda-2 is the most performant per-token open datas
 
 
 <center>
-<img src="https://cdn-uploads.huggingface.co/production/uploads/65c05e75c084467acab2f84a/YfOOh2JqRgkeHP1gHSSt9.png" width="600" alt="Zyda-2 evaluation scores">
+<img src="https://cdn-uploads.huggingface.co/production/uploads/65455aca468722e935103b17/-nxHBcU38QJ-MNdKXPiYS.png" width="600" alt="Zyda-2 evaluation scores">
 </center>
 
 
-
 For more information, please see our technical blog (-/TODO LINK)
 
 ## How to download
@@ -95,15 +94,15 @@ Each component has they're own individual schema. Please, consult with their res
 
 However, in all components the document text is in `text` column, and unique document document id is in `nemo_id` column.
 
-Our Zyda1 and Dolma-CC versions also have two additional columns corresponding to prediction of Nvidia's quality model (https://huggingface.co/nvidia/quality-classifier-deberta): `quality_prob` and `quality_pred`. 
+Our Zyda-1 and Dolma-CC versions also have two additional columns corresponding to prediction of Nvidia's quality model (https://huggingface.co/nvidia/quality-classifier-deberta): `quality_prob` and `quality_pred`. 
 
 ### Source Data
 
 Zyda-2 is comprised of four high quality open-source datasets:
 
-Zyda1: https://huggingface.co/datasets/Zyphra/Zyda
+Zyda-1: https://huggingface.co/datasets/Zyphra/Zyda
 
-Dolma-1.7-cc https://huggingface.co/datasets/allenai/dolma
+Dolma-CC v1.7: https://huggingface.co/datasets/allenai/dolma
 
 DCLM-baseline: https://huggingface.co/datasets/mlfoundations/dclm-baseline-1.0