meerkat-ml 0.2.6a2

Meerkat is building new data abstractions to make machine learning easier.

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Meerkat is a Python library aimed at technical teams that want to interactively wrangle their unstructured data with foundation models.

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⚡️ Quickstart

We recommend installing Meerkat in a fresh virtual environment,

conda create -n meerkat python=3.10 # or use your favorite virtual environment
conda activate meerkat
pip install meerkat-ml
mk install

GPU Install: If you want to use Meerkat with a GPU, you will need to install PyTorch with GPU support. See here for more details.

Optional Dependencies: some parts of Meerkat rely on optional dependencies e.g. audio processing may rely on utilities from torchaudio. We leave it up to you to install necessary dependencies when required. As a convenience, we provide bundles of optional dependencies that you can install e.g. pip install meerkat-ml[text] for text dependencies. See setup.py for a full list of optional dependencies.

Then try one of our demos,

mk demo match 
# mk demo --help to see a full list of available demos

(If this didn't work for you, we'd appreciate if you could open an issue and let us know.)

Next Steps. Check out our Getting Started page and our documentation to start building with Meerkat. As we work to make the documentation more comprehensive, please feel free to open an issue or reach out if you have any questions.

✉️ About

Meerkat is being developed at Stanford's Hazy Research Lab. Please reach out to kgoel [at] cs [dot] stanford [dot] edu, eyuboglu [at] stanford [dot] edu, and arjundd [at] stanford [dot] edu if you would like to use Meerkat for a project, at your company or if you have any questions.