Label data for machine learning models
Display CLIP benchmark results for inference performance
What happened in open-source AI this year, and whatโs next?
Uncensored General Intelligence Leaderboard
Analyze your dataset with guided tools
Analyze data to generate a comprehensive profile report
Browse and explore datasets from Hugging Face
Try the Hugging Face API through the playground
statistics analysis for linear regression
Classify breast cancer risk based on cell features
Display server status information
Profile a dataset and publish the report on Hugging Face
Multilingual metrics for the LMSys Arena Leaderboard
Mikeyandfriends-PixelWave FLUX.1-dev 03 is a data visualization tool designed to assist in labeling data for machine learning models. It provides an intuitive interface to help users organize, visualize, and annotate datasets, making it easier to prepare data for training machine learning models. This development version (03) includes experimental features aimed at improving efficiency and user experience.
Example: For a dataset of images, you can visualize the images, add labels, and export the labeled dataset for training a computer vision model.
What datasets is Mikeyandfriends-PixelWave FLUX.1-dev 03 compatible with?
The tool supports a wide range of datasets, including images, text, and numerical data. It is particularly optimized for image-based datasets.
Can I customize the labeling tools?
Yes, customizable labeling tools are available, allowing you to create workflows tailored to your specific dataset or project requirements.
What file formats does the tool support for exporting labeled data?
Mikeyandfriends-PixelWave FLUX.1-dev 03 supports common formats such as CSV, JSON, and COCO for seamless integration with machine learning pipelines.