Create README.md

README.md

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+---
+annotations_creators:
+- no-annotation
+language_creators:
+- crowdsourced
+language:
+- ko
+license:
+- cc-by-sa-4.0
+multilinguality:
+- monolingual
+pretty_name: KcBERT Pre-Training Corpus (Korean News Comments)
+size_categories:
+- 10M<n<100M
+source_datasets:
+- original
+task_categories:
+- fill-mask
+- text-generation
+task_ids:
+- masked-language-modeling
+- language-modeling
+---
+
+# KcBERT Pre-Training Corpus (Korean News Comments)
+
+## Dataset Description
+
+- **Homepage:** https://www.kaggle.com/datasets/junbumlee/kcbert-pretraining-corpus-korean-news-comments
+
+- **Repository:** https://github.com/Beomi/KcBERT
+
+- **Paper:** [Needs More Information]
+
+- **Leaderboard:** [Needs More Information]
+
+- **Point of Contact:** [Needs More Information]
+
+
+## KcBERT
+[beomi/kcbert-base](https://huggingface.co/beomi/kcbert-base)
+
+Github KcBERT Repo: [https://github.com/Beomi/KcBERT](https://github.com/Beomi/KcBERT)  
+KcBERT is Korean Comments BERT pretrained on this Corpus set.  
+(You can use it via Huggingface's Transformers library!)
+
+This Kaggle Dataset contains **CLEANED** dataset preprocessed with the code below.
+
+```python
+import re
+import emoji
+from soynlp.normalizer import repeat_normalize
+
+emojis = ''.join(emoji.UNICODE_EMOJI.keys())
+pattern = re.compile(f'[^ .,?!/@$%~％·∼()\x00-\x7Fㄱ-힣{emojis}]+')
+url_pattern = re.compile(
+    r'https?:\/\/(www\.)?[-a-zA-Z0-9@:%._\+~#=]{1,256}\.[a-zA-Z0-9()]{1,6}\b([-a-zA-Z0-9()@:%_\+.~#?&//=]*)')
+
+def clean(x):
+    x = pattern.sub(' ', x)
+    x = url_pattern.sub('', x)
+    x = x.strip()
+    x = repeat_normalize(x, num_repeats=2)
+    return x
+```
+
+### License
+[CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)
+
+## Dataset Structure
+### Data Instance
+```pycon
+>>> from datasets import load_dataset
+
+>>> dataset = load_dataset("Bingsu/KcBERT_Pre-Training_Corpus")
+>>> dataset
+DatasetDict({
+	train: Dataset({
+		features: ['text'],
+		num_rows: 86246285
+	})
+})
+```
+
+### Data Size
+download: 7.90 GiB
+generated: 11.86 GiB
+total: 19.76 GiB
+
+※ You can download this dataset from [kaggle](https://www.kaggle.com/datasets/junbumlee/kcbert-pretraining-corpus-korean-news-comments), and it's 5 GiB. (12.48 GiB when uncompressed)
+
+### Data Fields
+
+- text: `string`
+
+### Data Splits
+
+|            |   train  |
+| ---------- | -------- |
+| # of texts | 86246285 |