Support by Parquet, CSV, Jsonl, XLS
Label data for machine learning models
Convert a model to Safetensors and open a PR
Download datasets from a URL
Colabora para conseguir un Carnaval de Cádiz más accesible
Manage and analyze labeled datasets
Upload files to a Hugging Face repository
List of French datasets not referenced on the Hub
Generate a Parquet file for dataset validation
Review and rate queries
Manage and annotate datasets
Manage and label datasets for your projects
Display translation benchmark results from NTREX dataset
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.