Open source annotation tool for machine learning practitioners.
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Updated
Mar 6, 2024 - Python
Open source annotation tool for machine learning practitioners.
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.
A machine learning tool for automated prediction engineering. It allows you to easily structure prediction problems and generate labels for supervised learning.
Make drawing and labeling bounding boxes easy as cake
🚤 Label data at scale. Fun and precision included.
Toloka-Kit is a Python library for working with Toloka API.
Label data using HuggingFace's transformers and automatically get a prediction service
A library to synthesize text datasets using Large Language Models (LLM)
A Jupyter widget for annotating images with bounding boxes
Superpipe - optimized LLM pipelines for structured data
Design, conduct and analyze results of AI-powered surveys and experiments. Simulate social science and market research with large numbers of AI agents and LLMs.
A simple client for doccano API.
doccano auto labeling pipeline helps doccano to annotate a document automatically.
Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling
Heartex Python SDK - Connect your own models to Heartex Data Labeling
Client interface for all things Cleanlab Studio
Segments.ai Python SDK
Create training data labels from a production model with Modzy, Dropbox, and Label Studio
Tensorflow-Keras semantic segmentation
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