CoolFace
Datasetpublic

LyraNovaHeart/TheRoyalCarpet-Deduped-Compressed

The Royal Carpet: Cleaned Original Dataset: KaraKaraWitch/the-royal-carpet Thanks KaraKaraWitch! Why? The original dataset is 40GB in size (at least in decimal), which is quite the large set! 40GB would likely overwhelm most systems since I doubt most people have more than 32GB of RAM. Not to mention too, this dataset contained a redundant row, html, which is just a exact copy of the text row with HTML crap, removing that row brought down most of the dataset to… See the full description on the dataset page: https://huggingface.co/datasets/LyraNovaHeart/TheRoyalCarpet-Deduped-Compressed.

sourceHugging Faceupdated 9mo agoView on Hugging Face
0likes67downloads
Dataset Card

The Royal Carpet: Cleaned

Original Dataset: KaraKaraWitch/the-royal-carpet

Thanks KaraKaraWitch!

Why?

The original dataset is 40GB in size (at least in decimal), which is quite the large set! 40GB would likely overwhelm most systems since I doubt most people have more than 32GB of RAM. Not to mention too, this dataset contained a redundant row, html, which is just a exact copy of the text row with HTML crap, removing that row brought down most of the dataset to roughly... 15.2GB. I did check the dataset too, it looks like it cleanly removed just the HTML row, which means nothing else besides that got modified, as a side thing, I also compressed the set into 7-Zip archives to speed up the download process, which reduces it to just 4GB overall.

Download Links (For Convience)

JSONL Part 1: Download Part 2: Download Part 3: Download Part 4: Download

Total Size: 15.06GB (Binary), 16.17GB (Decimal)

7z

Part 1: Download Part 2: Download Part 3: Download Part 4: Download

Total Size: 3.81GB (Binary), 4.00GB (Decimal)

Code Used to Remove the Row

import json
def remove_columns_from_jsonl(input_file, output_file, columns_to_remove):
    """
    Remove specified columns from JSONL file.
    
    Args:
        input_file: Input JSONL file path
        output_file: Output JSONL file path
        columns_to_remove: List of column names to remove (e.g., ['html', 'other_column'])
    """
    with open(input_file, 'r', encoding='utf-8') as infile, \
         open(output_file, 'w', encoding='utf-8') as outfile:
        
        for line_num, line in enumerate(infile, 1):
            try:
                data = json.loads(line.strip())
                
                # Remove specified columns
                for column in columns_to_remove:
                    if column in data:
                        del data[column]
                
                # Write cleaned data
                outfile.write(json.dumps(data, ensure_ascii=False) + '\n')
                
            except json.JSONDecodeError as e:
                print(f"Error on line {line_num}: {e}")
        
        print(f"✓ Processed {line_num} lines")
        print(f"✓ Removed columns: {columns_to_remove}")

# Usage:
remove_columns_from_jsonl('TheRoyalCarpet-split-00.jsonl', 'cleaned-001.jsonl', ['html'])```



# Credit

KaraKaraWitch: [Profile](https://huggingface.co/KaraKaraWitch)