[Discussion] Look for service to upload a model and receive a REST API endpoint, for serving predictions

• huggingface_hub

  104 1,675 9.6 Python

  The official Python client for the Huggingface Hub.

  

You can try https://huggingface.co/ You can host and deploy any model, you can also host your datasets and private models.

• transformers

  175 125,021 10.0 Python

  🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

  

The library has more than 50k stars: https://github.com/huggingface/transformers

• 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.

  

• seldon-core

  14 4,212 7.8 HTML

  An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models

  

If you want to serve your model at scale, with a bunch of production features you should have a look at the open-source framework Seldon Core. It does what you're asking for plus a bunch of other cool stuff like routing, logging and monitoring.

• domino-research

  3 76 0.0 Python

  Projects developed by Domino's R&D team

  

(Disclosure, I am a maintainer on this project) You should checkout Bridge - it deploys models directly from an MLflow registry to SageMaker inference endpoints (hosted APIs). It basically turns your registry into a declarative source of truth for your hosting. The advantage of this approach is that it provides a clean way to update/upgrade your APIs from the same place you're tracking your new versions, experiments etc. One source of truth. You can get an MLflow registry up in a couple minutes if you don't have one.

Suggest a related project