Open source libraries for seamless integration into fully automated ML pipelines.
# Install the packagespip install -U toloka-kit crowd-kit
Our Python toolkit covers all API functionality to give you the full power of Toloka
Our open API gives you the freedom to integrate directly into any pipelines
Our Java client library provides a lightweight interface to the Toloka API that works in any Java enviroment
Check out our samples for detailed instructions on how to create and run each project using our Python library and retrieve the resulting dataset. Sample code is written in Jupyter Notebook, and we use Crowd-Kit for data aggregation.
Image classification
Image collection
Object detection
Side-by-side
Video collection
Categorical Responses | Textual Responses | Image Segmentation | Pairwise Comparisons |
---|---|---|---|
Majority Vote | RASA | Segmentation MV | Bradley-Terry |
Dawid-Skene | HRRASA | Segmentation RASA | Noisy Bradley-Terry |
Gold Majority Vote | ROVER | Segmentation EM | |
M-MSR | |||
Zero-Based Skill | |||
Wawa | |||
GLAD |
To experiment more with Crowd-Kit, see the documentation. Go to GitHub.