Build datasets using natural language
Organize and process datasets using AI
Upload files to a Hugging Face repository
Display trending datasets from Hugging Face
Create datasets with FAQs and SFT prompts
Create a report in BoAmps format
Display translation benchmark results from NTREX dataset
Display instructional dataset
Speech Corpus Creation Tool
List of French datasets not referenced on the Hub
Rename models in dataset leaderboard
Train a model using custom data
A Synthetic Data Generator is a powerful tool designed to build datasets using natural language. It enables users to generate synthetic datasets for training machine learning models, addressing data scarcity and privacy concerns by creating realistic, artificial data tailored to specific needs.
What types of data can I generate with Synthetic Data Generator?
You can generate text, images, tabular data, and more, depending on your specified requirements.
Is the generated data realistic enough for training models?
Yes, the synthetic data is designed to be highly realistic and suitable for training machine learning models effectively.
Can I customize the data to fit my specific needs?
Absolutely. You can define formats, schemas, and patterns to ensure the data aligns with your use case.