Show HN: Deploy ML Models on a Budget

• zenml

  33 3,657 9.8 Python

  ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.

  

Hey @sabalaba, that sounds pretty interesting. Would you be willing to integrate with ZenML? https://github.com/maiot-io/zenml . We're looking for solutions like that that have synergies

• budgetml

  4 1,332 0.0 Python

  Deploy a ML inference service on a budget in less than 10 lines of code.

  

• WorkOS

  workos.com sponsored

  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.

  

• onnxruntime

  54 12,656 10.0 C++

  ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

  

And ONNX helps too - https://github.com/microsoft/onnxruntime

• MLflow

  55 17,234 9.9 Python

  Open source platform for the machine learning lifecycle

  

How long have you used MLflow for what kind of models? Are you using it personally or do you use it as a team?

As far as I can tell, it cannot deploy models that use high dimensional input. It can log these models, and it can deploy them, but the "deployed" model can only accept two dimensional data.

This is an open issue[0] with open pull requests. We're experimenting with MLflow for our platform (https://iko.ai), but we automatically detect models, metrics, and parameters and then track that with MLflow instead of haivng people pollute their notebook code with MLflow code. We don't like leaking that detail (tracking code) into the notebook.

- [0]: https://github.com/mlflow/mlflow/issues/3570

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