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README.md

@@ -36,25 +36,25 @@ war, ceb, min, vie, ilo, tgl, lao, khm, mya, jav, ind, tha, sun, zlm
 ## Supported Tasks
 
 Self Supervised Pretraining
-    
+
 ## Dataset Usage
 ### Using `datasets` library
 ```
-    from datasets import load_dataset
-    dset = datasets.load_dataset("SEACrowd/oscar_2201", trust_remote_code=True)
+from datasets import load_dataset
+dset = datasets.load_dataset("SEACrowd/oscar_2201", trust_remote_code=True)
 ```
 ### Using `seacrowd` library
 ```import seacrowd as sc
 # Load the dataset using the default config
-    dset = sc.load_dataset("oscar_2201", schema="seacrowd")
+dset = sc.load_dataset("oscar_2201", schema="seacrowd")
 # Check all available subsets (config names) of the dataset
-    print(sc.available_config_names("oscar_2201"))
+print(sc.available_config_names("oscar_2201"))
 # Load the dataset using a specific config
-    dset = sc.load_dataset_by_config_name(config_name="<config_name>")
+dset = sc.load_dataset_by_config_name(config_name="<config_name>")
 ```
-    
-    More details on how to load the `seacrowd` library can be found [here](https://github.com/SEACrowd/seacrowd-datahub?tab=readme-ov-file#how-to-use).
-    
+
+More details on how to load the `seacrowd` library can be found [here](https://github.com/SEACrowd/seacrowd-datahub?tab=readme-ov-file#how-to-use).
+
 
 ## Dataset Homepage