🚀The Faster Library simplifies the deployment process of AI models like mistal and image classification.
🔧Copying and running the provided code in your favorite editor enables the deployment of the model.
🎯By changing the sampling parameter in the request body, you can customize the model's output.
⚡The model runs on a FastAPI server, which executes the requests and provides responses.
☁️The application can be deployed in the cloud and shared with others using a single command.
How does the Faster Library simplify model deployment?
—The Faster Library provides simple APIs that make it easier to deploy models like mistal and image classification.
What is the role of the sampling parameter?
—By changing the sampling parameter in the request body, you can control the output of the model.
What server does the model run on?
—The model runs on a FastAPI server, which executes the requests and provides responses.
Can the application be deployed in the cloud?
—Yes, the application can be deployed in the cloud and shared with others using a single command.
Is there a free GPU credit available?
—Yes, Lightning AI provides free GPU credits for users to enjoy.
00:00Introduction to deploying your own AI model using the Faster Library.
00:23Copying and running the provided code to deploy a mistal model.
00:37Accessing the API endpoint in the Swagger UI and customizing the sampling parameter.
00:48Running the request through the model using the execute button.
01:01Deploying the application in the cloud using a single command.
