Manage and annotate datasets
Search narrators and view network connections
Provide feedback on AI responses to prompts
Launch and explore labeled datasets
Explore and manage datasets for machine learning
Upload files to a Hugging Face repository
Review and rate queries
Support by Parquet, CSV, Jsonl, XLS
Transfer datasets from HuggingFace to ModelScope
Download datasets from a URL
Convert a model to Safetensors and open a PR
Browse TheBloke models' history
Create a domain-specific dataset seed
Argilla Space Template is a powerful tool designed for dataset creation and management. It helps users streamline the process of organizing, annotating, and preparing datasets for artificial intelligence and machine learning applications. The template provides a structured approach to dataset management, making it easier to handle complex data annotation tasks efficiently.
• Dataset Organization: Structured layout for organizing datasets in a clear and accessible manner. • Template-Based Annotation: Pre-designed templates to accelerate the annotation process. • Collaborative Features: Enables multiple users to work together on dataset creation and annotation. • Version Control: Track changes and maintain different versions of your datasets. • Integration with ML Pipelines: Seamlessly integrate with machine learning workflows for training and deployment.
1. Can I customize the templates to fit my specific needs?
Yes, Argilla Space Template allows you to customize the templates to suit your dataset requirements. You can modify the existing templates or create new ones.
2. How does collaboration work in Argilla Space Template?
Collaboration is straightforward. You can invite team members to work on the dataset, and changes are tracked in real-time. Version control ensures that everyone is working on the latest version.
3. What file formats are supported for export?
Argilla Space Template supports a variety of file formats, including JSON, CSV, and COCO, ensuring compatibility with most machine learning pipelines.