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README.md

@@ -19,16 +19,16 @@ Wisesight Sentiment Corpus: Social media messages in Thai language with sentimen
 * Time period: Around 2016 to early 2019. With small amount from other period.
 * Domains: Mixed. Majority are consumer products and services (restaurants, cosmetics, drinks, car, hotels), with some current affairs.
 * Privacy:
-    * Only messages that made available to the public on the internet (websites, blogs, social network sites).
-    * For Facebook, this means the public comments (everyone can see) that made on a public page.
-    * Private/protected messages and messages in groups, chat, and inbox are not included.
+* Only messages that made available to the public on the internet (websites, blogs, social network sites).
+* For Facebook, this means the public comments (everyone can see) that made on a public page.
+* Private/protected messages and messages in groups, chat, and inbox are not included.
 * Alternations and modifications:
-    * Keep in mind that this corpus does not statistically represent anything in the language register.
-    * Large amount of messages are not in their original form. Personal data are removed or masked.
-    * Duplicated, leading, and trailing whitespaces are removed. Other punctuations, symbols, and emojis are kept intact.
-    (Mis)spellings are kept intact.
-    * Messages longer than 2,000 characters are removed.
-    * Long non-Thai messages are removed. Duplicated message (exact match) are removed.
+* Keep in mind that this corpus does not statistically represent anything in the language register.
+* Large amount of messages are not in their original form. Personal data are removed or masked.
+* Duplicated, leading, and trailing whitespaces are removed. Other punctuations, symbols, and emojis are kept intact.
+(Mis)spellings are kept intact.
+* Messages longer than 2,000 characters are removed.
+* Long non-Thai messages are removed. Duplicated message (exact match) are removed.
 * More characteristics of the data can be explore: https://github.com/PyThaiNLP/wisesight-sentiment/blob/master/exploration.ipynb
 
 
@@ -39,25 +39,25 @@ tha
 ## Supported Tasks
 
 Sentiment Analysis
-    
+
 ## Dataset Usage
 ### Using `datasets` library
 ```
-    from datasets import load_dataset
-    dset = datasets.load_dataset("SEACrowd/wisesight_thai_sentiment", trust_remote_code=True)
+from datasets import load_dataset
+dset = datasets.load_dataset("SEACrowd/wisesight_thai_sentiment", trust_remote_code=True)
 ```
 ### Using `seacrowd` library
 ```import seacrowd as sc
 # Load the dataset using the default config
-    dset = sc.load_dataset("wisesight_thai_sentiment", schema="seacrowd")
+dset = sc.load_dataset("wisesight_thai_sentiment", schema="seacrowd")
 # Check all available subsets (config names) of the dataset
-    print(sc.available_config_names("wisesight_thai_sentiment"))
+print(sc.available_config_names("wisesight_thai_sentiment"))
 # 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