Support by Parquet, CSV, Jsonl, XLS
Display trending datasets and spaces
Create a report in BoAmps format
Label data for machine learning models
Organize and process datasets using AI
Browse and extract data from Hugging Face datasets
Create a domain-specific dataset project
Organize and process datasets efficiently
Find and view synthetic data pipelines on Hugging Face
Create datasets with FAQs and SFT prompts
Browse TheBloke models' history
Manage and label your datasets
Datasets Convertor is a powerful tool designed to simplify the process of converting datasets between different formats. Supported formats include Parquet, CSV, Jsonl, and XLS, making it a versatile solution for data professionals. Whether you need to transform data for analysis, storage, or integration with other systems, Datasets Convertor provides a robust and efficient way to manage your dataset conversions.
• Multiple Format Support: Convert between Parquet, CSV, Jsonl, and XLS formats seamlessly.
• Efficient Conversion: Designed for high-performance data transformation, ensuring quick conversion even for large datasets.
• User-Friendly Interface: Intuitive design makes it easy to select input files, choose output formats, and apply conversion settings.
• Customizable Options: Adjust settings such as encoding, delimiter, and schema to meet specific requirements.
• Cross-Platform Compatibility: Works on Windows, macOS, and Linux, catering to diverse operating environments.
What formats are supported by Datasets Convertor?
Datasets Convertor supports Parquet, CSV, Jsonl, and XLS formats for both input and output.
Can I customize the conversion settings?
Yes, Datasets Convertor allows customization of settings such as encoding, delimiters, and schema to ensure the conversion meets your specific requirements.
What is the advantage of using Parquet format?
Parquet is a columnar storage format that offers better compression and faster query performance, making it ideal for large-scale data analysis.
How do I handle large CSV files?
For large CSV files, use the batch processing feature in Datasets Convertor to ensure smooth and efficient conversion without performance issues.