Deploy your Serverless AI App in 10 Minutes with Code Engine
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Quickly deploy an AI-powered serverless app using IBM Code Engine. Learn step-by-step how to create and launch applications effortlessly.
At a Glance
Do you want to deploy a serverless AI model like a software engineer using technologies such as Docker containers and Kubernetes? This guided project will show you how to deploy a text-generation app based on the large GPT2 model in 10 mins. On the one hand, this project does not require knowledge of front-end and back-end development. On the other hand, the model deployment comes at no cost! You get free resources on IBM Cloud to experiment with deploying the AI model you like and share the app.
A Look at the Project Ahead
You will also use Gradio, a Python framework that allows you to build demos or interactive apps of your Machine Learning models, APIs, or Data Science workflows and share them. Gradio lets you quickly generate a user interface for your application with just a few lines of code, which means even without knowledge of HTML or CSS, you can still create a simple UI by calling its powerful Python APIs.
Learning Objectives:
- Know how to wrap a Machine Learning model inside Gradio’s interface.
- Understand containerization.
- Have hands-on experience with containerization.
- Become familiar with IBM Code Engine.
- Know how to use Code Engine to create and store container images on IBM Cloud.
- Deploy the Machine Learning app from the container image.
- Learn good practices and troubleshooting with IBM Code Engine.
What You’ll Need
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