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    Learning Interpretability Tool

    Learning Interpretability Tool

    Interactively analyze ML models to understand their behavior

    The Learning Interpretability Tool (LIT, formerly known as the Language Interpretability Tool) is a visual, interactive ML model-understanding tool that supports text, image, and tabular data. It can be run as a standalone server, or inside of notebook environments such as Colab, Jupyter, and Google Cloud Vertex AI notebooks.
    Downloads: 3 This Week
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