Update README.md

README.md

@@ -59,10 +59,10 @@ To download the whole dataset we recommend to either clone the repository, or, i
 Example command to clone the repository using huggingface-cli: `huggingface-cli download Zyphra/Zyda2-5T--repo-type dataset`
 
 Commands to download individual components:
- - DCLM: `ds = datasets.load_dataset("Zyphra/Zyda2-5T", name="dclm-crossdeduped", split="train")`
- - Zyda: `ds = datasets.load_dataset("Zyphra/Zyda2-5T", name="zyda-crossdeduped-filtered ", split="train")`
- - Dolma-CC: `ds = datasets.load_dataset("Zyphra/Zyda2-5T", name="dolma_cc-crossdeduped-filtered", split="train")`
- - Fineweb-Edu: `ds = datasets.load_dataset("Zyphra/Zyda2-5T", name="fwe3", split="train")`
+ - DCLM:  `ds = datasets.load_dataset("Zyphra/Zyda2-5T", name="dclm-crossdeduped", split="train")`
+ - Zyda:  `ds = datasets.load_dataset("Zyphra/Zyda2-5T", name="zyda-crossdeduped-filtered", split="train")`
+ - Dolma-CC:  `ds = datasets.load_dataset("Zyphra/Zyda2-5T", name="dolma_cc-crossdeduped-filtered", split="train")`
+ - Fineweb-Edu:  `ds = datasets.load_dataset("Zyphra/Zyda2-5T", name="fwe3", split="train")`
 
 In this repository we provide raw results of cross deduplication and filtering. To achieve the best possible performance, one will need to appropriate weights during training.
 We found the following optimal weights (in the sense of weights in the resultant dataset): DCLM - 4.0, FWE3 - 4.0, Zyda - 0.16, Dolma-CC - 0.24.