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README.md

@@ -14,7 +14,7 @@ tags:
 ---
 
 
-BasahaCorpus contains short stories in four Central Philippine languages     (Minasbate, Rinconada, Kinaray-a, and Hiligaynon) for low-resource     readability assessment. Each dataset per language contains stories     distributed over the first three grade levels (L1, L2, and L3) in     the Philippine education context. The grade levels of the dataset     have been provided by an expert from Let's Read Asia.
+BasahaCorpus contains short stories in four Central Philippine languages(Minasbate, Rinconada, Kinaray-a, and Hiligaynon) for low-resourcereadability assessment. Each dataset per language contains storiesdistributed over the first three grade levels (L1, L2, and L3) inthe Philippine education context. The grade levels of the datasethave been provided by an expert from Let's Read Asia.
 
 
 ## Languages
@@ -24,25 +24,25 @@ msb, rin, kar, hil
 ## Supported Tasks
 
 Readability Assessment
-    
+
 ## Dataset Usage
 ### Using `datasets` library
 ```
-    from datasets import load_dataset
-    dset = datasets.load_dataset("SEACrowd/basaha_corpus", trust_remote_code=True)
+from datasets import load_dataset
+dset = datasets.load_dataset("SEACrowd/basaha_corpus", trust_remote_code=True)
 ```
 ### Using `seacrowd` library
 ```import seacrowd as sc
 # Load the dataset using the default config
-    dset = sc.load_dataset("basaha_corpus", schema="seacrowd")
+dset = sc.load_dataset("basaha_corpus", schema="seacrowd")
 # Check all available subsets (config names) of the dataset
-    print(sc.available_config_names("basaha_corpus"))
+print(sc.available_config_names("basaha_corpus"))
 # 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