Showing 3 open source projects for "dv-work"

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    Cleanlab

    Cleanlab

    The standard data-centric AI package for data quality and ML

    ...See some of the datasets cleaned with cleanlab at labelerrors.com. This package helps you find label issues and other data issues, so you can train reliable ML models. All features of cleanlab work with any dataset and any model. Yes, any model: PyTorch, Tensorflow, Keras, JAX, HuggingFace, OpenAI, XGBoost, scikit-learn, etc. If you use a sklearn-compatible classifier, all cleanlab methods work out-of-the-box.
    Downloads: 6 This Week
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  • 2
    Toloka-Kit

    Toloka-Kit

    Toloka-Kit is a Python library for working with Toloka API

    ...Toloka entities are represented as Python classes. You can use them instead of accessing the API using JSON representations. There’s no need to validate JSON files and work with them directly. Support of both synchronous and asynchronous (via async/await) executions. Streaming support: build complex pipelines which send and receive data in real-time. For example, you can pass data between two related projects: one for data labeling, and another for its validation. AutoQuality feature which automatically finds the best fitting quality control rules for your project.
    Downloads: 2 This Week
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  • 3
    Adala

    Adala

    Adala: Autonomous DAta (Labeling) Agent framework

    Adala is a data-centric AI framework focused on dataset curation, annotation, and validation. It helps AI teams manage high-quality training datasets by providing tools for data auditing, error detection, and quality assessment.
    Downloads: 0 This Week
    Last Update:
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