Hey! Builder of Model Zoo here.
I've worked as a software engineer in machine learning for a few years, bringing models to production in a variety of areas. Although there exists an open-source ecosystem for deploying ML models, most of these tools are targeted towards infrastructure engineers -- Kubernetes, Docker, and web server frameworks. As a result, there exists a gap today between some of the data scientists and machine learning engineers that develop these models and the skills required to deploy them.
I built Model Zoo to address that gap. Deploy your model to an HTTP endpoint with a single line of code, from any Python environment. Plus, you get all the features you'll need from a production ML system for free (monitoring features / predictions, autoscaling, web interface for documentation).
You can experiment with it in-browser via Google Colaboratory or in your own Python environment:
https://docs.modelzoo.dev/quickstart/tensorflow.html or https://docs.modelzoo.dev/quickstart/transformers.html
reply