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README.md

@@ -9,12 +9,12 @@ tags:
 - self-supervised-pretraining
 ---
 
-    Indo4B is a large-scale Indonesian self-supervised pre-training corpus
-    consists of around 3.6B words, with around 250M sentences. The corpus
-    covers both formal and colloquial Indonesian sentences compiled from 
-    12 sources, of which two cover Indonesian colloquial language, eight
-    cover formal Indonesian language, and the rest have a mixed style of
-    both colloquial and formal.
+Indo4B is a large-scale Indonesian self-supervised pre-training corpus
+consists of around 3.6B words, with around 250M sentences. The corpus
+covers both formal and colloquial Indonesian sentences compiled from 
+12 sources, of which two cover Indonesian colloquial language, eight
+cover formal Indonesian language, and the rest have a mixed style of
+both colloquial and formal.
 
 
 ## Languages
@@ -24,25 +24,25 @@ ind
 ## Supported Tasks
 
 Self Supervised Pretraining
-    
+
 ## Dataset Usage
 ### Using `datasets` library
 ```
-    from datasets import load_dataset
-    dset = datasets.load_dataset("SEACrowd/indo4b", trust_remote_code=True)
+from datasets import load_dataset
+dset = datasets.load_dataset("SEACrowd/indo4b", trust_remote_code=True)
 ```
 ### Using `seacrowd` library
 ```import seacrowd as sc
 # Load the dataset using the default config
-    dset = sc.load_dataset("indo4b", schema="seacrowd")
+dset = sc.load_dataset("indo4b", schema="seacrowd")
 # Check all available subsets (config names) of the dataset
-    print(sc.available_config_names("indo4b"))
+print(sc.available_config_names("indo4b"))
 # 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