Label data for machine learning models
This project is a GUI for the gpustack/gguf-parser-go
Transfer GitHub repositories to Hugging Face Spaces
Check system health
More advanced and challenging multi-task evaluation
Check your progress in a Deep RL course
Evaluate model predictions and update leaderboard
Display a Bokeh plot
Display and analyze PyTorch Image Models leaderboard
Evaluate diversity in data sets to improve fairness
Analyze Shark Tank India episodes
Leaderboard for text-to-video generation models
Generate detailed data reports
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.