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README.md

@@ -11,7 +11,7 @@ tags:
 ---
 
 
-This is an automatically-produced question answering dataset     generated from Indonesian Wikipedia articles. Each entry     in the dataset consists of a context paragraph, the     question and answer, and the question's equivalent SPARQL     query. Questions are separated into two subsets: simple     (question consists of a single SPARQL triple pattern) and     complex (question consists of two triples plus an optional     typing triple).
+This is an automatically-produced question answering datasetgenerated from Indonesian Wikipedia articles. Each entryin the dataset consists of a context paragraph, thequestion and answer, and the question's equivalent SPARQLquery. Questions are separated into two subsets: simple(question consists of a single SPARQL triple pattern) andcomplex (question consists of two triples plus an optionaltyping triple).
 
 
 ## Languages
@@ -21,25 +21,25 @@ ind
 ## Supported Tasks
 
 Question Answering
-    
+
 ## Dataset Usage
 ### Using `datasets` library
 ```
-    from datasets import load_dataset
-    dset = datasets.load_dataset("SEACrowd/ac_iquad", trust_remote_code=True)
+from datasets import load_dataset
+dset = datasets.load_dataset("SEACrowd/ac_iquad", trust_remote_code=True)
 ```
 ### Using `seacrowd` library
 ```import seacrowd as sc
 # Load the dataset using the default config
-    dset = sc.load_dataset("ac_iquad", schema="seacrowd")
+dset = sc.load_dataset("ac_iquad", schema="seacrowd")
 # Check all available subsets (config names) of the dataset
-    print(sc.available_config_names("ac_iquad"))
+print(sc.available_config_names("ac_iquad"))
 # 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