User Guide#

Welcome to the 3LC User Guide. This document provides an overview of the system’s components, their roles, and how they interact with each other. You’ll find instructions on how to use 3LC alongside different machine learning frameworks and models, and guidance on sharing datasets among users.

Overview#

Using 3LC with your own data begins in your notebook or Python script. Powerful visualization tools, collection and analysis of custom metrics, and seamless editing of your dataset can all be unlocked with just 3 Lines of Code.

  1. Import the tlc Python package:

    import tlc

  2. Create a Table object from your dataset:

    ...
dataset = tlc.Table.from_torch_dataset(dataset, ...)
...

  3. Collect metrics to analyze in the 3LC Dashboard:

    ...
tlc.collect_metrics(dataset, ...)
...

Integrations#

Or jump straight to one of our integration user guides to see how 3LC can be used with your favorite machine learning framework:

YOLO v5      YOLO v8      Hugging Face      Detectron2      PyTorch Lightning

Table of Contents#

Or dive into the details of the 3LC system with our in-depth user guide sections: