Follow this guide to learn how to deploy your model with FastAPI using a Gradient Deployment. Readers should expect to learn how to upload their trained model as a Gradient model artifact, create a Docker image that will serve their model, and deploy their image on Gradient using a deployment.
In this tutorial, we show how Whisper can be used with MoviePy to automatically generate and overlay translated subtitles from any video sample. We then walked through setting up this process to run both within a Notebook context and from an application served with Gradient Deployments.
Follow this guide to learn how to integrate Arize within Gradient Deployments to monitor data drift, traffic, and other model monitoring metrics.
This guide demonstrates what the Gradient Deployments resource is capable of, and provides a succinct guide to creating your own deployment and interacting with it using Workflows.
In part two of deploying deep learning models, learn how to host on Paperspace.
