Launch and explore labeled datasets
Convert and PR models to Safetensors
Create a domain-specific dataset project
Upload files to a Hugging Face repository
Train a model using custom data
Display translation benchmark results from NTREX dataset
Generate synthetic datasets for AI training
Create and validate structured metadata for datasets
Display trending datasets from Hugging Face
ReWrite datasets with a text instruction
Perform OSINT analysis, fetch URL titles, fine-tune models
Display trending datasets and spaces
CSQA is a powerful tool designed for dataset creation and exploration. It simplifies the process of managing and preparing datasets for AI/ML models by providing an intuitive interface to launch and explore labeled datasets. Whether you're a data scientist, researcher, or AI practitioner, CSQA helps streamline your workflow by automating and organizing dataset-related tasks.
• Automated Data Labeling: Efficiently label datasets with AI-powered tools.
• Dataset Versioning: Track changes and maintain multiple versions of your datasets.
• Advanced Search: Quickly find specific data points within large datasets.
• Collaboration Tools: Work with teams seamlessly with shared access and real-time updates.
• Integration: Compatible with popular AI/ML frameworks for easy model training.
• Customizable Workflows: Tailor the platform to fit your specific dataset needs.
• User-Friendly Interface: Navigate and manage datasets with an intuitive design.
What systems does CSQA support?
CSQA is compatible with Windows, macOS, and Linux operating systems, as well as cloud-based environments.
Can I customize the labeling process?
Yes, CSQA allows you to create custom labeling workflows tailored to your project requirements.
Is CSQA suitable for large-scale datasets?
Absolutely! CSQA is optimized to handle large datasets efficiently, with scalable solutions for data management and exploration.