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🍌 Banana Serverless Whisper Template

This repo gives a basic framework for serving OpenAI's Whisper in production using simple HTTP servers.

If you want to generalize this to deploy anything on Banana, see the guide here.

Look at test.py for instructions on how to call this model on locally as well as deployed on banana.

Move to prod:

At this point, you have a functioning http server for your ML model. You can use it as is, or package it up with our provided Dockerfile and deploy it to your favorite container hosting provider!

If Banana is your favorite GPU hosting provider, read on!

🍌

Deploy to Banana Serverless:

Three steps:

  1. Create your own copy of this template repo. Either:
  • Click "Fork" (creates a public repo)
  • Click "Use this Template" (creates a private or public repo)
  • Create your own repo and copy the template files into it
  1. Login in to the Banana Dashboard and setup your account by saving your payment details and linking your Github.

From then onward, any pushes to the default repo branch (usually "main" or "master") trigger Banana to build and deploy your server, using the Dockerfile. Throughout the build we'll sprinkle in some secret sauce to make your server extra snappy 🔥

It'll then be deployed on our Serverless GPU cluster and callable with any of our serverside SDKs:

You can monitor buildtime and runtime logs by clicking the logs button in the model view on the Banana Dashboard](https://app.banana.dev)


Use Banana for scale.

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  • Python 85.4%
  • Dockerfile 14.6%