I'm trying to serve an ML Model as REST API using TensorFlow Serving. I want to know whether there's a way to host the model online rather than locally?
I need to host a ML model where there's a mapping going with a string id when doing predictions. The model is a .h5 file. The program runs in a notebook. But I don't know how to do the hosting, when developing the mobile app.
Probably the easiest solution would be to pack your model into a docker container and host it on any VPS like AWS EC2 or DigitalOcean.
There is a medium article that describes the process of creating the container. It is rather old, but should be mostly relevant even today.
Serving ML Quickly with TensorFlow Serving and Docker
After you have your container, you can follow any guide that describes how to publish it to the cloud.
For example:
Deploy to AWS, Docker in 10 Minutes! | by Milan McGraw | Geek Culture | Medium
Also, if you do not strictly need to use tf serving, you could look into some projects specifically designed to ease the deployment process like BentoML. I am confident there are plenty of guides online that describe how to host the app on any platform.