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README.md
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- self-supervised-pretraining
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---
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## Languages
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## Supported Tasks
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Self Supervised Pretraining
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## Dataset Usage
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### Using `datasets` library
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```
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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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# Check all available subsets (config names) of the dataset
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# Load the dataset using a specific config
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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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## 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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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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## Dataset Homepage
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