Running Serverless ML on AWS Lambda

This page summarizes the projects mentioned and recommended in the original post on dev.to

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  • Pytorch

    Tensors and Dynamic neural networks in Python with strong GPU acceleration

    Then we add the 🤗 Hugging Face transformers library mentioned above, specifying it should also install the PyTorch ML framework it will use under the hood.

  • Poetry

    Python packaging and dependency management made easy

    For dependency management, we will use Poetry. Why not pip? Because Poetry is better in every aspect.

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

  • git-lfs

    Git extension for versioning large files

    Because the pre-trained model is large, around 1 GB, we need a Git LFS extension installed to download it. Then we run:

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