Upload files to a Hugging Face repository
Browse and view Hugging Face datasets from a collection
Manage and orchestrate AI workflows and datasets
Save user inputs to datasets on Hugging Face
Organize and process datasets for AI models
Create and validate structured metadata for datasets
Convert a model to Safetensors and open a PR
Create a report in BoAmps format
Build datasets and workflows using AI models
Train a model using custom data
Explore recent datasets from Hugging Face Hub
Data annotation for Sparky
Clean and process datasets
Dadada is a dataset creation tool designed to simplify the process of uploading and managing files for machine learning projects. It allows users to seamlessly upload their files to a Hugging Face repository, making it easier to organize and share datasets for AI model training.
• File Upload: Supports uploading various file types such as text, images, and CSV.
• Hugging Face Integration: Directly integrates with Hugging Face repositories for streamlined dataset management.
• Dataset Management: Organize datasets with custom naming and tagging options.
• Privacy Controls: Set public or private access for uploaded datasets.
• Collaboration Tools: Share datasets with collaborators using Hugging Face's built-in sharing features.
• Access Controls: Ensure secure access with granular permissions for different users or teams.
What file types does Dadada support?
Dadada supports a wide range of file types, including text, images, CSV, and more, making it versatile for various machine learning projects.
Do I need to register to use Dadada?
Yes, you need to create an account or log in to use Dadada's features and manage your datasets.
Where are my datasets stored?
Your datasets are stored in your Hugging Face repository, ensuring they are accessible and shareable through Hugging Face's platform.