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@@ -11,9 +11,9 @@ tags:
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  - self-supervised-pretraining
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  ---
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- Indo4B-Plus is an extension of Indo4B, a large-scale Indonesian self-supervised pre-training corpus.
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- Indo4B-Plus extend Indo4B by adding two low-resource Indonesian local languages to the corpus, i.e., Sundanese and Javanese.
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- Indo4B-Plus adds 82,582,025 words (∼2.07%) of Sundanese sentences and 331,041,877 words (∼8.29%) of Javanese
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  ## Languages
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  ## Supported Tasks
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  Self Supervised Pretraining
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-
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  ## Dataset Usage
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  ### Using `datasets` library
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  ```
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- from datasets import load_dataset
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- dset = datasets.load_dataset("SEACrowd/indo4b_plus", trust_remote_code=True)
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  ```
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  ### Using `seacrowd` library
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  ```import seacrowd as sc
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  # Load the dataset using the default config
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- dset = sc.load_dataset("indo4b_plus", schema="seacrowd")
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  # Check all available subsets (config names) of the dataset
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- print(sc.available_config_names("indo4b_plus"))
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  # Load the dataset using a specific config
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- dset = sc.load_dataset_by_config_name(config_name="<config_name>")
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  ```
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-
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- 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).
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-
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  ## Dataset Homepage
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  - self-supervised-pretraining
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  ---
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+ Indo4B-Plus is an extension of Indo4B, a large-scale Indonesian self-supervised pre-training corpus.
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+ Indo4B-Plus extend Indo4B by adding two low-resource Indonesian local languages to the corpus, i.e., Sundanese and Javanese.
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+ Indo4B-Plus adds 82,582,025 words (∼2.07%) of Sundanese sentences and 331,041,877 words (∼8.29%) of Javanese
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  ## Languages
 
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  ## Supported Tasks
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  Self Supervised Pretraining
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+
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  ## Dataset Usage
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  ### Using `datasets` library
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  ```
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+ from datasets import load_dataset
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+ dset = datasets.load_dataset("SEACrowd/indo4b_plus", trust_remote_code=True)
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  ```
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  ### Using `seacrowd` library
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  ```import seacrowd as sc
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  # Load the dataset using the default config
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+ dset = sc.load_dataset("indo4b_plus", schema="seacrowd")
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  # Check all available subsets (config names) of the dataset
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+ print(sc.available_config_names("indo4b_plus"))
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  # Load the dataset using a specific config
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+ dset = sc.load_dataset_by_config_name(config_name="<config_name>")
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  ```
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+
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+ 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).
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+
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  ## Dataset Homepage
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